MCA Full Course Journey – 2 Years ka Complete Vlog! 📚🔥

 

🎓 MCA Full Course Journey – Complete Q&A                                  (Vlog Style)

Q1. MCA kya hota hai?

Ans: MCA ka full form Master of Computer Applications hai. Ye 2 saal ka professional IT post-graduation course hai jisme programming, software development, AI, data science, web development, networking, cybersecurity sab cover hota hai.

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Q2. MCA ki duration kitni hoti hai?

Ans: Pehle 3 years hoti thi, lekin ab 2 years ka course hai (4 semesters).

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Q3. MCA ke liye eligibility kya hai?

Ans:

• Graduation (BCA / BSc IT / BSc CS / BCom / BA / BBA)

• Maths compulsory ya 12th me Math hona chahiye (college ke rules depend karte hain).

• Minimum 50% marks.

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Q4. MCA me kya-kya subjects hote hain?

Ans:
Semester 1: C/C++, DBMS, CN, OS, Maths
Semester 2: Java/Python, DSA, Web Dev, OOPs
Semester 3: Advanced Java/Python, Cloud, ML Basics
Semester 4: Internship + Major Project

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Q5. MCA me coding zaroori hoti hai?

Ans: Yes! MCA mostly coding-based hota hai.
Aapko kam se kam Java ya Python achhe se aani chahiye.

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Q6. MCA ke baad kaise jobs milti hain?

Ans:

• Software Developer

• Full Stack Developer

• Java/Python Developer

• Data Analyst

• Cloud Engineer

• QA Tester

• Cyber Security Analyst

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Q7. MCA ke baad salary kitni milti hai?

Ans: Freshers: 4 LPA – 8 LPA
Experience: 10 LPA – 25 LPA (skill-based)

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Q8. MCA ke liye best programming language kaunsi?

Ans:

1. Java

2. Python

3. C++ (DSA ke liye helpful)

Video suggestion: “Java vs Python – MCA Students ke liye kaun best?”

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Q9. MCA me project kitne important hote hain?

Ans: Bahut important!
Aapka Major Project hi aapko internship + job me help karta hai.
Good Projects:

• Web App

• Android App

• ML Model

• CRM Software

• E-Commerce Site

• Attendance + Face Recognition System

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Q10. MCA me internship kaise milti hai?

Ans:

• College placement

• LinkedIn

• Internshala

• Apne projects aur GitHub se profile strong karke

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Q11. MCA ke saath kaun-kaun online courses karne chahiye?

Ans:

• Data Structures & Algorithms

• Java / Python

• SQL + MongoDB

• Web Development

• Cloud Basics (AWS / Azure)

• Git & GitHub

• Machine Learning basics

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Q12. MCA entrance exams kaun-kaun se hote hain?

Ans:

• NIMCET (Top exam)

• CUET PG

• BHU PET

• MAH MCA CET

• TANCET

• IPU CET

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Q13. MCA difficult hota hai kya?

Ans: Agar coding ka interest hai to easy hai.
Interest nahi hai → thoda tough lagega.
But practice se sab possible hai.

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Q14. MCA ke best colleges kaun-kaun se hain?

Ans:

• NITs (Top)

• BHU

• VIT

• JNU

• Pune University

• IPU Colleges

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Q15. MCA vs MTech – kaunsa better?

Ans:

• MCA = Software & Coding oriented

• MTech = Research & Core specialization
  Agar developer banna hai → MCA Best
  Research / Academics → MTech Best

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Q16. MCA karne ke main benefits kya hai?

Ans:

• IT me high-paying jobs

• Fast career growth

• Masters degree advantage

• Internship + Live Projects

• Strong programming skills

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Q17. MCA me maths high-level hoti hai kya?

Ans: Bas basic maths hoti hai — matrix, logic, discrete maths.
PhD level maths nahi hoti.

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Q18. MCA ke baad kya higher studies kar sakte hain?

Ans: Yes!

• PhD

• MBA

• MTech (Specialization karna ho to)

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Q19. MCA student ka daily routine kaisa hota hai?

Ans:

• 10 AM: Class (Programming / DBMS)

• 2 PM: Lab Session

• 6 PM: Coding practice

• Weekend: Projects + Assignments

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Q20. MCA karna worth it hai kya?

Ans: Bilkul!
Aaj ke time me software industry booming hai, MCA graduates ki demand high hai.
Aapke paas skill ho → Package guaranteed hai.

🎓 MCA Full Course Questions & Answers – Part 2 (Vlog Script)

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Q21. MCA ki fees kitni hoti hai?

Ans: College par depend karta hai.

• Government colleges: 20,000 – 80,000 per year

• Private colleges: 1 lakh – 2.5 lakh per year

• NITs: Around 1 lakh per year

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Q22. MCA me attendance compulsory hoti hai?

Ans:
Haan, majority colleges me 75% attendance mandatory hoti hai.
Lekin practical subjects me attendance aur strict hoti hai.

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Q23. MCA me theory zyada hoti hai ya practical?

Ans:
MCA almost 60% practical + 40% theory hota hai.
Projects aur coding hi main focus hote hain.

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Q24. MCA me laptop zaroori hota hai kya?

Ans:
100% Yes!
Programming, projects, labs, assignments sab ke liye laptop hona mandatory hai.

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Q25. MCA ke liye best laptop specs kya honi chahiye?

Ans:

• i5/i7 or Ryzen 5/7

• 8GB/16GB RAM

• SSD (256GB / 512GB)

• Good battery
  Programming ke liye heavy GPU zaroori nahi.

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Q26. MCA me kitna coding practice karna padta hai?

Ans:
Aapko daily 1–2 hours coding karni chahiye.
Job-level skills ke liye 6 months me coding strong ho jaati hai.

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Q27. MCA ke exams difficult hote hain kya?

Ans:
Normal difficulty hoti hai.
Agar aap classes attend karte ho + notes banate ho to pass hona easy hai.

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Q28. MCA me kaise marks milte hain?

Ans:

• Internal exams

• Assignments

• Viva

• Practical exams

• Final semester theory exams
  Total milke final score banta hai.

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Q29. MCA internship paid hoti hai ya unpaid?

Ans:
Both!

• Startups: Unpaid / low stipend

• Mid-level companies: 5k–15k stipend

• MNCs: 15k–30k stipend

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Q30. MCA me placement hota hai kya?

Ans:
Haan, achhe colleges me placement strong hota hai.
Companies aati hain:

• TCS

• Infosys

• Wipro

• Accenture

• Cognizant

• Capgemini

• Product companies (college par depend karta hai)

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Q31. MCA ke liye best specialization kaun-sa hai?

Ans:

• Data Science

• Full Stack Development

• Cloud Computing

• Cyber Security

• ML / AI

• Mobile App Development

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Q32. MCA fresher ko job milna mushkil hota hai kya?

Ans:
Nahi!
Agar skills + projects + GitHub strong ho → 100% job milti hai.

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Q33. MCA ke baad Govt jobs milti hain kya?

Ans:
Yes!

• SSC jobs

• Banking (PO / Clerk)

• Railways

• ISRO

• NIC

• DRDO

• UPSC (if interested)

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Q34. MCA vs BTech – difference kya hai?

Ans:
MCA: Post-graduation, coding-focused
BTech: Engineering + broad technical study
Jobs dono ko equal milti hain.

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Q35. MCA me English zaroori hoti hai kya?

Ans:
Basic English required hoti hai kyunki coding language, errors, documentation sab English me hote hain.

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Q36. MCA me kitna maths aata hai?

Ans:
Only basic + computer maths:

• Matrix

• Logic

• Discrete Maths

• Probability basics
  Hardcore maths nahi hoti.

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Q37. MCA ka best time-table kya hona chahiye?

Ans:

• 2 hrs → Coding

• 1 hr → DSA

• 1 hr → Projects

• Weekend → Revision + GitHub

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Q38. MCA ke saath part-time job kar sakte hain?

Ans:
Haan, online freelancing, teaching, coding support kar sakte ho.
Lekin full-time job + MCA (regular) mushkil hota hai.

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Q39. MCA ke baad foreign jobs milti hain kya?

Ans:
Yes!
Agar aapke paas experience + strong skills ho to US/Canada/UK me jobs mil sakti hain.

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Q40. MCA worth it hai ya nahi?

Ans:
Agar aapka goal IT me career banana hai
aur aap coding seekhna chahte ho → MCA is 100% worth it.

🎓 MCA Full Course – Q&A Part 3 (Vlog Script Ready)

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Q41. MCA ke top entrance exams kaise clear karte hain?

Ans:
Preparation ke liye:

• Class 11–12 ka Maths revise karo

• Logical reasoning practice

• Basic programming (C / Java)

• Previous year papers solve karo
  Most important exam: NIMCET (Top MCA colleges ke liye)

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Q42. MCA entrance me kya-kya aata hai?

Ans:

• Maths (Hard Level)

• Reasoning

• English

• Computer Awareness

• Basic Programming Concepts

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Q43. MCA students ko college life kaisi hoti hai?

Ans:
Bahut chill + practical oriented life hoti hai:

• Coding labs

• Project work

• Group presentations

• Hackathon participation

• Internship hunt
  College me competition zyada hota hai, but fun bhi utna hi.

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Q44. MCA me notes kaise banaye?

Ans:

• Har subject ke short notes banao

• Programming ke liye separate copy rakho

• DBMS + CN ke diagrams draw karo

• Exam ke liye last 20 days notes gold jaisa kaam karte hain

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Q45. MCA ke viva kaise hote hain?

Ans:
Viva mostly practical based hota hai:

• Aapka code explain karna

• Database schema

• Project idea

• Output ki working
  Viva me confidence sabse important hota hai.

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Q46. MCA me DSA kitna important hota hai?

Ans:
DSA is life-changing.
Agar DSA strong hai → Campus placement easy.
Topics:

• Arrays

• Strings

• Linked List

• Trees

• Sorting

• Searching

• Recursion

• Dynamic Programming

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Q47. MCA me kaunsa project best hota hai?

Ans:
TOP PROJECT IDEAS:

• Hospital Management System

• E-Commerce Web App

• Face Recognition Attendance System

• Chatting Application

• Loan Eligibility ML Model

• College Management App

• Delivery Tracking App

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Q48. MCA major project kis language me banana chahiye?

Ans:
Best languages:

• Java Spring Boot

• Python Django / Flask

• PHP Laravel

• MERN Stack

• Android (Java/Kotlin)

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Q49. MCA placement interview me kya pucha jata hai?

Ans:

• OOPs Concepts

• SQL Queries

• DSA basics

• Final year project

• 10–15 MCQ

• HR questions
  Aapke communication skills ka bhi test hota hai.

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Q50. MCA student ke liye resume kaise hona chahiye?

Ans:

• Skills

• Projects

• Certifications

• GitHub link

• LinkedIn link

• Education
  Freshers ke liye projects sabse strong point hote hain.

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Q51. MCA me coding nahi aati ho to kaise start karein?

Ans:

• YouTube se basics

• Java ya Python choose karo

• 30 days coding challenge

• Daily 1–2 hours practice
  3 months me coding confidence aa jata hai.

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Q52. MCA ke saath part-time freelancing kaise karein?

Ans:
Platforms:

• Fiverr

• Upwork

• Freelancer
  Start with:

• Web design

• Small apps

• Data entry

• Bug fixing

• Website maintenance

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Q53. MCA me backlog aa jaye to problem hoti hai?

Ans:
Nahi, backlog common hota hai.
Make sure next attempt me clear kar do.
Final placement me backlog tab problem banega agar graduate time pe nahi ho paate.

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Q54. MCA ke baad sab log coding field me hi jate hain?

Ans:
Nahi!
MCA ke baad role options:

• DevOps

• QA Testing

• UI/UX

• Data Analyst

• IT Support

• System Admin

• Cloud Operations
  Har skill ka scope hai.

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Q55. Kya MCA karne ke baad MNC me job mil sakti hai?

Ans:
100% YES!
MCA students TCS, Accenture, Infosys, Cognizant, Capgemini me easily placed hote hain.

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Q56. MCA private college se karna sahi hai kya?

Ans:
Agar:

• Coding training mile

• Internship mile

• Placement cell active ho
  To private college bhi best hai.
  College ka naam itna important nahi → Skill important hai.

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Q57. MCA late karne se career slow hota hai kya?

Ans:
Bilkul nahi.
IT field me skills > age hota hai.
25–30 age me bhi log MCA karke high salary jobs lete hain.

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Q58. MCA ke baad startup join karna good option hai?

Ans:
Yes!
Startups me:

• Fast growth

• Multiple skills

• Real experience

• Good salary
  Bahut kuch seekhne ko milta hai.

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Q59. MCA me networking (friends & seniors) kitni important hoti hai?

Ans:
Bahut zyada important!

• Seniors internship dilate hain

• Friends ke sath projects bante hain

• Referrals milte hain

• Support मिलता है

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Q60. MCA ke baad future kaisa hai?

Ans:
Future is super bright → IT is booming!
AI, Cloud, Data Science, Full Stack, Cyber Security me massive opportunities hain.

🎓 MCA Full Course – Q&A Part 4 (61–100)

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Q61. MCA me sabse tough subject kaunsa hota hai?

Ans: Students ke hisaab se tough subjects:

• Data Structures

• Discrete Mathematics

• Computer Networks

• Java Programming
  Tough tab lagta hai agar practice nahi karo.

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Q62. MCA me easiest subject kaunsa hota hai?

Ans:

• Web Development

• DBMS

• Software Engineering

• Operating System basics
  Ye subjects usually easy lagte hain.

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Q63. MCA ke first semester me kya hota hai?

Ans:

• Basic programming

• Maths

• OS

• DBMS

• Networking basics
  First sem foundation banata hai.

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Q64. MCA me attendance kaise manage karein?

Ans:

• Morning classes skip mat karo

• Practical classes compulsory attend karo

• Proxy avoid karo (caught = debar bhi ho sakte ho!)

• 75% maintain karo

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Q65. MCA viva me sabse zyada kya pucha jata hai?

Ans:

1. Code explain karo

2. Query run karo

3. Output ka meaning

4. Logic kaise implement kiya

5. Project ka idea kaise aaya

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Q66. MCA me programming nahi aati ho to fail ho jaayenge?

Ans:
Bilkul nahi!
Start slow, but consistent raho.
3–4 months daily coding → sab clear ho jayega.

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Q67. MCA me syllabus zyada hota hai kya?

Ans:
Haan, moderate to heavy syllabus hota hai.
But practical based hone ke wajah se interesting hota hai.

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Q68. MCA ke practical exams kaise hote hain?

Ans:

• System allotted hota hai

• Question milta hai (code likho)

• Output run karna hota hai

• Viva hota hai

• Pass hone ke liye working code zaroori

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Q69. MCA me group projects milte hain kya?

Ans:
Haan, group projects milte hain jisme 3–5 log milkar kaam karte hain.
Teamwork + communication improve hota hai.

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Q70. MCA ke liye best coding platform kaun-sa?

Ans:

• LeetCode

• HackerRank

• CodeStudio

• CodeChef

• GFG (GeeksforGeeks)

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Q71. MCA me kitne projects banana padte hain?

Ans:

• 2 mini projects

• 1 major project

• 1 internship project
  Total 3–4 projects recommended.

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Q72. MCA ke baad fresher ko kitna package milta hai?

Ans:

• Normal college: 3–5 LPA

• Good college: 5–8 LPA

• Top college: 8–15 LPA
  Skill-based field hai.

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Q73. MCA ke saath coding kaise improve karein?

Ans:

• Daily 1 coding question

• Java/Python ek language choose karo

• DSA 3 months roadmap follow karo

• Projects banao → confidence boost

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Q74. MCA me hostel life kaisi hoti hai?

Ans:

• Fun + Stress mix

• Night coding

• Group study

• Events

• Late-night Maggie
  Bahut yaadein banti hain.

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Q75. MCA ke liye best specialization kya hota hai?

Ans:

• Full Stack Development

• Data Science

• Cloud Computing

• Cyber Security

• DevOps
  Sab future-proof fields hain.

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Q76. MCA student ka portfolio kaise hona chahiye?

Ans:

• 3 projects

• GitHub

• LinkedIn

• Resume

• Certification

• Personal website (optional but great)

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Q77. MCA ke baad entrepreneurship kar sakte hain?

Ans:
Bilkul!
Aap khud ka startup, freelancing agency, software firm shuru kar sakte ho.

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Q78. MCA me coding language kaise choose karein?

Ans:

• Java → Placement friendly

• Python → ML + Data Science ke liye best

• C++ → DSA ke liye best
  Choose 1 main language + 1 support language.

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Q79. MCA ke liye most important skill kya hai?

Ans:
Problem Solving + Logic Building
Programming tabhi aati hai.

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Q80. MCA me Kya English weak hone se problem hoti hai?

Ans:
Sirf starting me.
Coding English pe depend nahi — logic pe depend karta hai.
Gradually improve ho jaati hai.

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Q81. MCA ke baad jobs kaise search karein?

Ans:

• LinkedIn

• Naukri

• Indeed

• Company career pages

• References

• Campus placement
  Projects dikhaoge → call zaroor aayenge.

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Q82. MCA private college se placement milta hai kya?

Ans:
Yes, agar:

• Projects strong hain

• Resume good

• Coding average to good level ka hai
  Skill > College

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Q83. MCA me backlog ka impact hota hai kya?

Ans:
Only tab hota hai jab:

• Backlog final year tak clear na ho
  Otherwise koi problem nahi.

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Q84. MCA me industrial tour hota hai kya?

Ans:
Some colleges yes.
You visit IT companies to learn real-world working.

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Q85. MCA ka timetable tough hota hai kya?

Ans:
Moderate:

• Morning lectures

• Afternoon labs

• Evening coding
  Time manage karna seekhna padta hai.

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Q86. MCA me maths tough hoti hai kya?

Ans:
Nahi, engineering-level nahi hoti.
Basics + logic oriented hoti hai.

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Q87. MCA ke liye reference books kaun-si best hain?

Ans:

• Java: Herbert Schildt

• DSA: Narasimha Karumanchi

• DBMS: Korth

• CN: Tanenbaum

• OS: Galvin

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Q88. MCA internship me kya work hota hai?

Ans:

• Web Development

• Testing

• Database handling

• API integration

• Small features develop karna

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Q89. MCA me presentation important hoti hai?

Ans:
Yes — internal marks me help karta hai + communication improve hota hai.

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Q90. MCA student ke liye communication skills zaroori hain?

Ans:
Yes, interviews me bohot kaam aate hain.
But perfect English required nahi.

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Q91. MCA me coding shorts ya cheat-sheets chalegi?

Ans:
Yes, but exam me nahi.
Learning ke liye bohot useful.

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Q92. MCA ke baad online jobs mil sakti hain kya?

Ans:
Yes:

• Freelancing

• Remote developer

• Data entry

• QA testing

• Internships

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Q93. MCA me networking (friends/seniors) se kya fayda?

Ans:

• Project help

• Referral

• Placement tips

• Notes & previous year papers

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Q94. MCA me self-study important hai?

Ans:
College ke sath 40% self-study compulsory hai.

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Q95. MCA me laptop coding ke alawa aur kya work hota hai?

Ans:

• Presentations

• Research

• Project documentation

• GitHub uploads

• Notes typing

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Q96. MCA student ko hackathon join karna chahiye?

Ans:
100% YES!

• Skills improve

• Projects banenge

• Resume powerful banega

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Q97. MCA ke fees ka loan milta hai kya?

Ans:
Yes, education loan mil jata hai — especially government colleges me.

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Q98. MCA ke baad PR (Canada/UK) possible hai?

Ans:
Yes, IT skills ki demand high hai.

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Q99. MCA practical file banana compulsory hoti hai kya?

Ans:
Yes.
File submit karna practical marks ke liye mandatory hota hai.

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Q100. MCA student ka future secure hota hai kya?

Ans:
YES!
IT field rising hai → Software jobs har saal badh rahi hain.
MCA student ka career extremely bright hota hai.

🎙️ MCA Vlog Script – Part 5 (Continue)

Q&A Format

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Q18: MCA me Internship kab hoti hai?

A:
Usually MCA ke last semester me 5–6 months ki industrial training hoti hai.
Aap real companies me kaam karte ho jaise:

• Software Development

• Web Development

• Android Development

• Data Science

• Cloud & DevOps

• Cyber Security

• AI & ML

Internship se aapka real experience start hota hai.

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Q19: Internship kaise milti hai?

A:
Internship ke 4 best sources:

1️⃣ College Placement Cell
2️⃣ LinkedIn Jobs
3️⃣ Internshala
4️⃣ Company Websites (Careers Page)

Aapko ek clean resume + GitHub portfolio banana zaruri hota hai.

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Q20: Internship me kya kaam karna padta hai?

A:
Internship me aapko milta hai:

• Real projects

• Daily tasks

• Stand-up meetings

• Testing

• Bug fixing

• Module development

• Documentation

Team ke sath real environment me kaam seekhne ka mauka milta hai.

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Q21: MCA ke baad kaunsi jobs milti hain?

A:
Top Job Roles:

• Software Developer

• Web Developer

• Android Developer

• Full-Stack Developer

• Backend Developer (Java/Python/.NET)

• Data Analyst / Scientist

• Cloud Engineer

• DevOps Engineer

• Cyber Security Analyst

• UI/UX Designer

• Database Administrator

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Q22: MCA ke baad salary kitni hoti hai?

A:
Freshers salary range:

Role	Salary Range
Software Developer	₹3.5–7 LPA
Web Developer	₹3–6 LPA
Android Developer	₹4–8 LPA
Data Analyst	₹5–10 LPA
Cloud/DevOps	₹6–12 LPA

Agar aap skills strong rakhte ho to package high mil sakta hai.

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Q23: MCA placement ke liye kaunse skills must hai?

A:
Placement cracking ke 6 weapons:

• DSA (Data Structures & Algorithms)

• OOP Concepts

• SQL + Database Skills

• Git & GitHub

• Communication Skills

• Real Projects (2–4 minimum)

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Q24: MCA ke andar kitne projects banane chahiye?

A:
Minimum:

• 2 Major Projects

• 3–4 Minor Projects

Strong portfolio → Strong placement chance.

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Q25: MCA karte time kaunsi mistakes avoid karni chahiye?

A:

❌ Sirf theory padhna
❌ Copy-paste project banana
❌ Placement ke time coding skills weak
❌ Internship ko lightly lena
❌ GitHub, LinkedIn profile na banana

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Q26: MCA me coding kaise improve kare?

A:

Daily 1–2 hour coding karo:

• LeetCode

• HackerRank

• CodeStudio

• GeeksForGeeks Practice

Initially easy → medium → hard questions.

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Q27: MCA ke baad abroad ja sakte hain?

A:
100% ja sakte ho!

MCA ke baad:

• MS in CS

• Job in foreign countries

• Remote jobs

Sab possible hai, bas skills strong honi chahiye.

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Q28: MCA ke top career paths kaunse hain?

A:

🌟 Software Development
🌟 Data Science / AI / ML
🌟 Cloud & DevOps
🌟 Cyber Security
🌟 Full-Stack Development
🌟 Game Development

Aaj ke time sab booming sectors hain.

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Q29: MCA ke liye roadmap kya hona chahiye? (Full Roadmap)

A:

Year 1

• Programming basics: C / Java / Python

• DBMS, SQL

• Web basics: HTML, CSS, JS

• Data Structures

Year 2

• Advanced programming

• Projects

• Internship

• Placement preparation

• Specialization choose karo (Java | Python | Android | Data Science | Cloud)

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Q30: MCA ke baad future kaisa hota hai?

A:
MCA is one of the most future-proof degrees in India.
Demand for IT jobs huge hai, especially skilled developers ke liye.

Agar aap skillful ho → career guaranteed

✅ SEMESTER 1 – Q&A SET (Q1–Q100)

COMPUTER FUNDAMENTALS

Q1. Computer kya hota hai?

A: Ek electronic machine jo data ko process karta hai.

Q2. CPU ka full form?

A: Central Processing Unit.

Q3. RAM kya hai?

A: Volatile memory jisme temporary data store hota hai.

Q4. ROM kya hota hai?

A: Non-volatile memory jisme permanent instructions stored hoti hain.

Q5. Software kya hota hai?

A: Instructions ka set jo computer ko kaam karne deta hai.

Q6. Operating System kya karta hai?

A: Hardware aur user ke beech communication provide karta hai.

Q7. Open-source OS example?

A: Linux.

Q8. Input device ka example?

A: Keyboard, mouse.

Q9. Output device ka example?

A: Monitor, printer.

Q10. ALU kya hota hai?

A: Arithmetic Logic Unit — calculations handle karta hai.

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PROGRAMMING IN C

Q11. C language kisne banayi?

A: Dennis Ritchie.

Q12. C ka compiler kaun sa hota hai?

A: GCC (GNU Compiler Collection).

Q13. Escape sequence “\n” kya karta hai?

A: New line start karta hai.

Q14. Identifier kya hota hai?

A: Variable, function ka naam.

Q15. int ka size kitna hota hai?

A: 2 or 4 bytes (system dependent).

Q16. printf() function ka kaam?

A: Output display karta hai.

Q17. scanf() ka use?

A: User input read karta hai.

Q18. Loop kya hota hai?

A: Repeated execution ke liye statement block.

Q19. for loop syntax?

for(initialization; condition; increment)

Q20. Array kya hota hai?

A: Same type ke elements ka collection.

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MATHEMATICS – DISCRETE MATH

Q21. Set kya hota hai?

A: Unique elements ka collection.

Q22. Null set kya hota hai?

A: Jisme koi element na ho.

Q23. Union of sets kya hota hai?

A: Dono sets ke unique elements ka set.

Q24. Intersection kya hota hai?

A: Common elements ka set.

Q25. Function kya hota hai?

A: Relation jisme har input ka ek output hota hai.

Q26. Graph kya hota hai?

A: Nodes aur edges ka structure.

Q27. Tree kya hota hai?

A: Acyclic connected graph.

Q28. Permutation kya hai?

A: Arrangements of objects (order matters).

Q29. Combination kya hai?

A: Selection of objects (order doesn’t matter).

Q30. Probability kya hoti hai?

A: Chances of an event (0 to 1).

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DBMS BASICS

Q31. DBMS ka full form?

A: Database Management System.

Q32. Database kya hota hai?

A: Organized data collection.

Q33. Table kya hoti hai?

A: Rows & columns ka structure.

Q34. Primary key kya hoti hai?

A: Unique identifier for rows.

Q35. Foreign key kya hoti hai?

A: Reference key of another table.

Q36. SQL ka full form?

A: Structured Query Language.

Q37. SELECT query example?

SELECT * FROM students;

Q38. Normalization kya hoti hai?

A: Redundancy remove karna.

Q39. 1NF kya hoti hai?

A: No repeating groups.

Q40. 3NF condition?

A: No transitive dependency.

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DIGITAL LOGIC

Q41. Binary number system kya hai?

A: Base-2 system (0 and 1).

Q42. AND gate output kab 1 hota hai?

A: Jab dono inputs 1 ho.

Q43. OR gate kab 1 deta hai?

A: Jab koi ek input 1 ho.

Q44. NOT gate kya karta hai?

A: Input ko invert.

Q45. Flip-flop kya hota hai?

A: 1-bit memory element.

Q46. Truth table kya hoti hai?

A: Input-output representation.

Q47. Decoder kya hota hai?

A: Binary to N-line conversion.

Q48. Multiplexer kya hota hai?

A: Multiple inputs → single output.

Q49. De-Mux kya hota hai?

A: Single input → multiple outputs.

Q50. Registers kya hotay hain?

A: CPU ki fast temporary storage.

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SOFTWARE ENGINEERING BASICS

Q51. Software Engineering kya hai?

A: Systematic software development process.

Q52. SDLC ka full form?

A: Software Development Life Cycle.

Q53. SDLC ke stages?

A: Requirement → Design → Coding → Testing → Deployment.

Q54. Waterfall model kya hai?

A: Linear development model.

Q55. Agile kya hota hai?

A: Iterative development methodology.

Q56. SRS kya hai?

A: Software Requirement Specification.

Q57. Testing kya hoti hai?

A: Errors find karna.

Q58. Unit testing kya hoti hai?

A: Individual units test karna.

Q59. Integration testing?

A: Modules ko saath test karna.

Q60. Validation kya hota hai?

A: Product meets user needs.

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CORE CS CONCEPTS

Q61. Algorithm kya hota hai?

A: Step-by-step procedure.

Q62. Flowchart kya hota hai?

A: Graphical algorithm representation.

Q63. Data kya hota hai?

A: Raw facts.

Q64. Information kya hai?

A: Processed data.

Q65. Compiler kya karta hai?

A: Code ko machine language me convert karta hai.

Q66. Interpreter kya karta hai?

A: Line-by-line execution.

Q67. Bit kya hai?

A: Smallest data unit (0/1).

Q68. Byte kitne bits ka hota hai?

A: 8 bits.

Q69. IP address kya hota hai?

A: Network device identifier.

Q70. URL kya hota hai?

A: Web address.

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MORE C LANGUAGE Q&A

Q71. Function kya hota hai?

A: Reusable block of code.

Q72. Call by value kya hai?

A: Value copy pass hoti hai.

Q73. Pointer kya hota hai?

A: Variable jo address store karta hai.

Q74. malloc() ka use?

A: Dynamic memory allocation.

Q75. free() function?

A: Memory deallocate.

Q76. String kya hai?

A: Character array.

Q77. Recursion kya hota hai?

A: Function calling itself.

Q78. Structure kya hai?

A: Different data types ka group.

Q79. Union kya hota hai?

A: Shared memory structure.

Q80. File handling functions?

A: fopen(), fclose(), fprintf()…

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EXTRA THEORY

Q81. LAN kya hota hai?

A: Local area network.

Q82. WAN kya hota hai?

A: Wide area network.

Q83. Internet kya hai?

A: Global network.

Q84. Modem kya karta hai?

A: Modulation & demodulation.

Q85. Virus kya hota hai?

A: Malicious software.

Q86. Firewall kya hota hai?

A: Security filter.

Q87. Cloud computing kya hai?

A: Internet-based services.

Q88. AI kya hota hai?

A: Machine intelligence.

Q89. Machine Learning kya hota hai?

A: Pattern learning system.

Q90. Big data kya hai?

A: Large volume of data.

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MATHEMATICS EXTRA

Q91. Matrix kya hota hai?

A: Rows & columns ka rectangular array.

Q92. Determinant kya hota hai?

A: Value used for solving equations.

Q93. Vector kya hota hai?

A: Quantity with magnitude & direction.

Q94. Limit kya hoti hai?

A: Approaching value.

Q95. Differential kya hota hai?

A: Rate of change.

Q96. Integration kya hai?

A: Area calculation process.

Q97. Logarithm kya hota hai?

A: Power representation.

Q98. Mapping kya hoti hai?

A: Input-output assignment.

Q99. Relation kya hota hai?

A: Set of ordered pairs.

Q100. Cardinality kya hoti hai?

A: Number of elements.

📚 MCA SEMESTER-1 – 500 Q&A

✅ PART 2 – Q101 to Q200

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🔵 PROGRAMMING IN C (Advanced)

Q101. C language me header file ka use kya hai?

A: Predefined functions aur declarations ko include karne ke liye.

Q102. stdio.h kis ke liye use hoti hai?

A: Input/Output functions jaise printf(), scanf().

Q103. Comment kaise likhte hain C me?

A:

• Single line: //

• Multi-line: /* */

Q104. Variable kya hota hai?

A: Data store karne wala named memory location.

Q105. Global variable kya hota hai?

A: Function ke bahar declared variable, sabko accessible.

Q106. Local variable?

A: Function ke andar declared, sirf us function me valid.

Q107. Constant kaise banate hain?

#define PI 3.14

Q108. sizeof operator kya karta hai?

A: Variable ya datatype ki size return karta hai.

Q109. Logical operators kaun kaun se hote hain?

A: && (AND), || (OR), ! (NOT)

Q110. Ternary operator syntax?

condition ? true : false;

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🔵 DIGITAL LOGIC – Advanced

Q111. Boolean algebra kya hota hai?

A: Logic operations ka mathematical system.

Q112. Boolean variables kitne values le sakte hain?

A: 2 values: 0 ya 1.

Q113. NAND gate ka special feature kya hai?

A: It is universal gate.

Q114. NOR gate universal gate kyu bolte hain?

A: Isse sab gates ban sakte hain.

Q115. K-map kya hota hai?

A: Boolean expression simplify karne ka tool.

Q116. Full adder kya karta hai?

A: 3 inputs ko add karta hai.

Q117. Half adder me carry hota hai?

A: Haan, carry generate hoti hai but previous carry add nahi hoti.

Q118. SR flip-flop problematic state?

A: S=1, R=1 (Invalid).

Q119. JK flip-flop kis problem ko solve karta hai?

A: SR flip-flop ki invalid state.

Q120. T flip-flop ka function?

A: Toggle state.

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🔵 DBMS – Deep Concepts

Q121. Schema kya hota hai?

A: Database ka logical structure.

Q122. Instance kya hota hai?

A: Particular time pe stored data.

Q123. Tuple kya hota hai?

A: Row of table.

Q124. Attribute kya hota hai?

A: Column of table.

Q125. Domain kya hota hai?

A: Allowed values ka set.

Q126. Candidate key kya hoti hai?

A: Primary key ban sakne wale keys.

Q127. Composite key kya hoti hai?

A: Multiple columns se banti key.

Q128. Super key kya hoti hai?

A: Any key that uniquely identifies a row.

Q129. SQL me COUNT() kya karta hai?

A: Row count return karta hai.

Q130. DISTINCT keyword ka use?

A: Duplicate values remove karna.

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🔵 C LANGUAGE – Loop & Arrays

Q131. break statement kya karta hai?

A: Loop ko terminate karta hai.

Q132. continue statement ka use?

A: Current iteration skip karta hai.

Q133. Infinite loop ka example?

while(1) {}

Q134. Two-dimensional array example?

int a[3][3];

Q135. Array index start kis se hota hai?

A: 0 se.

Q136. String terminating character?

A: '\0'

Q137. strcmp() ka kaam?

A: Strings compare karna.

Q138. strcpy() ka use?

A: String copy karna.

Q139. strlen() kya return karta hai?

A: String length (excluding '\0').

Q140. strcat() ka use?

A: Strings ko combine karna.

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🔵 MATHEMATICS – Advanced Discrete

Q141. Relation symmetric kab hota hai?

A: Jab (a, b) → (b, a) ho.

Q142. Reflexive relation ki condition?

A: (a, a) sab elements ke liye.

Q143. Transitive relation?

A: (a, b) & (b, c) → (a, c)

Q144. Equivalence relation?

A: Reflexive + Symmetric + Transitive.

Q145. HCF & LCM ke relation?

A: HCF × LCM = a × b

Q146. Graph me degree kya hoti hai?

A: Number of edges touching node.

Q147. Complete graph kya hota hai?

A: Every node connected to every other node.

Q148. Path kya hota hai?

A: Nodes ka sequence.

Q149. Cycle kya hota hai?

A: Closed path.

Q150. Bipartite graph?

A: Nodes 2 sets me divided.

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🔵 SOFTWARE ENGINEERING – Extended

Q151. Feasibility study kya hoti hai?

A: Project possible hai ya nahi.

Q152. Functional requirement?

A: System kya karega.

Q153. Non-functional requirement?

A: Performance, security, usability.

Q154. Prototype model kya hota hai?

A: Dummy model build karna.

Q155. Spiral model kis ke liye use hota hai?

A: High-risk projects.

Q156. Black box testing?

A: Internal code dekhe bina testing.

Q157. White box testing?

A: Code level testing.

Q158. Regression testing?

A: Change ke baad purana code check karna.

Q159. Debugging kya hota hai?

A: Error find + fix.

Q160. Maintenance types?

A: Corrective, Adaptive, Perfective.

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🔵 MORE C LANGUAGE – Pointers

Q161. Pointer declaration example?

int *p;

Q162. & operator kya deta hai?

A: Address of variable.

Q163. * operator kya karta hai?

A: Pointer dereference.

Q164. Null pointer kya hota hai?

A: Address = 0.

Q165. Dangling pointer?

A: Freed memory ka pointer.

Q166. Pointer to pointer example?

int **pp;

Q167. Function pointer?

A: Function ka address store karta hai.

Q168. Pointer arithmetic allowed?

A: Yes (addition/subtraction).

Q169. Array pointer ka base address?

A: Array ka starting address.

Q170. void pointer?

A: Generic pointer (any type).

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🔵 NETWORKING BASICS

Q171. Protocol kya hota hai?

A: Communication rules.

Q172. TCP ka full form?

A: Transmission Control Protocol.

Q173. UDP kaisa protocol hai?

A: Fast but connectionless.

Q174. HTTP port number?

A: 80

Q175. HTTPS port number?

A: 443

Q176. FTP ka port?

A: 21

Q177. DNS ka function?

A: Domain → IP conversion.

Q178. Router kya hota hai?

A: Networks ko connect karta hai.

Q179. Switch kya karta hai?

A: LAN me devices connect karta hai.

Q180. Firewall ka use?

A: Unauthorized access block.

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🔵 C LANGUAGE – FILE HANDLING

Q181. fopen() kya return karta hai?

A: FILE pointer.

Q182. File opening modes?

A: r, w, a, r+, w+, a+

Q183. fclose() ka use?

A: File close karna.

Q184. fprintf() kya karta hai?

A: File me formatted data write.

Q185. fscanf() ka use?

A: File se data read.

Q186. fputc() ka kaam?

A: Character write.

Q187. fgetc() ka kaam?

A: Character read.

Q188. EOF kya hota hai?

A: End of file.

Q189. File pointer movement ka function?

A: fseek()

Q190. ftell() ka use?

A: File pointer ki current position.

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🔵 EXTRA THEORY

Q191. Compiler error kab aata hai?

A: Syntax mistake.

Q192. Runtime error kab aata hai?

A: Program run ke time mistake.

Q193. Logical error?

A: Output wrong but program runs.

Q194. Data type ka purpose?

A: Data ki type define karna.

Q195. API kya hota hai?

A: Software-to-software interface.

Q196. IDE kya hota hai?

A: Programming environment.

Q197. ASCII kya hota hai?

A: Character encoding standard.

Q198. Unicode kya hai?

A: Universal character set.

Q199. Hexadecimal base?

A: 16

Q200. Binary to decimal convert kaise karte hain?

A: (Bit × 2^position) ka sum.

🎓 **MCA Semester-1

Q201 – Q300 (100 Question–Answers)**
Subjects Covered:
✔ C Programming
✔ DBMS
✔ Operating System
✔ Computer Networks
✔ Mathematics / Discrete Structures

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✅ Q201–Q300 STARTS

Q201. What is a preprocessor directive in C?

Ans: A command that begins with # and is processed before compilation (e.g., #include, #define).

Q202. What is typedef in C?

Ans: It creates an alias (new name) for a data type.

Q203. What is a nested structure in C?

Ans: A structure defined inside another structure.

Q204. What is DBMS normalization?

Ans: A process to reduce redundancy and avoid anomalies.

Q205. What is 1NF?

Ans: Each cell contains atomic (single) value only.

Q206. Define 2NF.

Ans: No partial dependency on a non-key attribute.

Q207. Define 3NF.

Ans: No transitive dependency; dependency only on key.

Q208. What is BCNF?

Ans: Every determinant must be a candidate key.

Q209. What is a transaction in DBMS?

Ans: A sequence of operations performed as a single logical unit.

Q210. What is ACID?

Ans:
A – Atomicity
C – Consistency
I – Isolation
D – Durability

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Q211. What is a Deadlock?

Ans: When two or more processes wait for each other forever.

Q212. Conditions for Deadlock?

Ans: Mutual exclusion, Hold and wait, No preemption, Circular wait.

Q213. What is a semaphore?

Ans: A synchronization tool used to control access to shared resources.

Q214. Types of semaphores?

Ans: Binary semaphore, Counting semaphore.

Q215. What is Round Robin scheduling?

Ans: Each process gets equal time slice in cyclic order.

Q216. What is Paging?

Ans: Memory management technique that divides memory into equal-sized blocks (pages).

Q217. What is Fragmentation?

Ans: Waste of memory. Two types: Internal and External.

Q218. What is Thrashing?

Ans: Too much swapping causing low CPU utilization.

Q219. What is Process Control Block (PCB)?

Ans: Data structure storing a process’s information.

Q220. What is a System Call?

Ans: Interface that allows user programs to interact with OS.

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Q221. What is a Computer Network?

Ans: Set of connected devices to share data/resources.

Q222. Types of networks?

Ans: LAN, MAN, WAN, PAN.

Q223. What is IP address?

Ans: A unique address to identify a device on a network.

Q224. IPv4 address size?

Ans: 32 bits.

Q225. IPv6 address size?

Ans: 128 bits.

Q226. What is a Router?

Ans: Device used to connect two or more networks.

Q227. What is a Switch?

Ans: Device to connect multiple devices in a LAN.

Q228. What is DNS?

Ans: Domain Name System – converts domain names to IP addresses.

Q229. What is URL?

Ans: Uniform Resource Locator – web address of a resource.

Q230. What is Bandwidth?

Ans: Maximum data transfer capacity of a network.

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Q231. What is a Graph in discrete math?

Ans: Collection of vertices and edges.

Q232. Types of Graphs?

Ans: Directed, Undirected, Weighted, Unweighted.

Q233. What is a Tree?

Ans: Connected acyclic graph.

Q234. What is a Degree of a vertex?

Ans: Number of edges incident to a vertex.

Q235. What is Permutation?

Ans: Arrangement of objects in order.

Q236. What is Combination?

Ans: Selection of objects without order.

Q237. Define Set.

Ans: A collection of distinct elements.

Q238. What is Universal Set?

Ans: Set containing all elements under consideration.

Q239. What is Subset?

Ans: If every element of A is in B, then A ⊆ B.

Q240. What is Power Set?

Ans: Set of all subsets of a set.

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Q241. What is a pointer in C?

Ans: A variable that stores memory address.

Q242. What is pointer arithmetic?

Ans: Operations like ptr + 1, ptr - 1.

Q243. What is malloc()?

Ans: Allocates memory at runtime.

Q244. What is calloc()?

Ans: Allocates multiple blocks and initializes with zero.

Q245. What is free()?

Ans: Deallocates memory.

Q246. What is realloc()?

Ans: Resizes previously allocated memory.

Q247. What is a File Pointer?

Ans: Pointer of type FILE* used in file handling.

Q248. What is fopen()?

Ans: Opens a file.

Q249. What is fprintf()?

Ans: Writes formatted output to a file.

Q250. What is fscanf()?

Ans: Reads formatted data from a file.

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Q251. What is a Relational Model in DBMS?

Ans: Represents data in the form of tables.

Q252. What is Cardinality?

Ans: Number of rows in a table.

Q253. What is Degree?

Ans: Number of columns in a table.

Q254. What is Referential Integrity?

Ans: Ensures foreign key value exists in parent table.

Q255. What is a Candidate Key?

Ans: Minimal set of attributes uniquely identifying rows.

Q256. What is a Composite Key?

Ans: Key formed using multiple columns.

Q257. What is a Primary Key?

Ans: Unique + Not Null identifier.

Q258. What is a Foreign Key?

Ans: Column that refers to primary key of another table.

Q259. What is a Unique Key?

Ans: Ensures all values are unique, allows null.

Q260. What is a View?

Ans: Virtual table created from other tables.

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Q261. What is a Scheduler?

Ans: OS component that decides process execution order.

Q262. What is CPU Burst?

Ans: Time period when process uses CPU.

Q263. What is IO Burst?

Ans: Time period when process waits for IO.

Q264. What is FCFS?

Ans: First Come First Serve scheduling.

Q265. What is SJF?

Ans: Shortest Job First scheduling.

Q266. What is Priority Scheduling?

Ans: CPU assigned based on priority.

Q267. What is Context Switching?

Ans: Saving and loading process states.

Q268. What is Virtual Memory?

Ans: Allows using more memory than physically available.

Q269. What is a Frame?

Ans: Fixed-sized block in physical memory.

Q270. What is a Page Table?

Ans: Maps virtual pages to physical frames.

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Q271. What is HTTP?

Ans: Hypertext Transfer Protocol – used for communication on web.

Q272. What is HTTPS?

Ans: Secure version of HTTP using SSL/TLS.

Q273. What is MAC Address?

Ans: Unique hardware address of network device.

Q274. What is Subnet Mask?

Ans: Used to divide network into subnets.

Q275. What is TCP?

Ans: Reliable, connection-oriented protocol.

Q276. What is UDP?

Ans: Fast, connectionless protocol.

Q277. What is OSI Model?

Ans: 7-layer network model.

Q278. Name OSI layers.

Ans: Physical, Data Link, Network, Transport, Session, Presentation, Application.

Q279. What is SMTP?

Ans: Email sending protocol.

Q280. What is POP3?

Ans: Email receiving protocol.

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Q281. What is a Set Union?

Ans: A ∪ B = elements in A or B.

Q282. What is an Intersection?

Ans: A ∩ B = elements common to both.

Q283. What is Set Difference?

Ans: A – B = elements in A but not in B.

Q284. Define Function in discrete math.

Ans: Relation where every input has exactly one output.

Q285. What is Injective function?

Ans: One-to-one mapping.

Q286. What is Surjective function?

Ans: Onto mapping.

Q287. What is Bijective function?

Ans: Both one-to-one AND onto.

Q288. What is a Mathematical Relation?

Ans: Set of ordered pairs.

Q289. What is Reflexive relation?

Ans: (a,a) exists for all elements.

Q290. What is Symmetric relation?

Ans: If (a,b) exists then (b,a) also exists.

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Q291. What is Asymmetric relation?

Ans: If (a,b) exists, (b,a) cannot exist.

Q292. What is Transitive relation?

Ans: (a,b) and (b,c) → (a,c)

Q293. What is Equivalence relation?

Ans: Reflexive + Symmetric + Transitive.

Q294. What is a Boolean Algebra?

Ans: Algebra of 0 and 1 with AND, OR, NOT.

Q295. What is a Truth Table?

Ans: Table showing all possible inputs and outputs.

Q296. What is a Tautology?

Ans: Expression always TRUE.

Q297. What is a Contradiction?

Ans: Expression always FALSE.

Q298. What is a Contingency?

Ans: Expression sometimes true, sometimes false.

Q299. What is a Propositional Logic?

Ans: Logic dealing with propositions and connectives.

Q300. What is Predicate Logic?

Ans: Logic using quantifiers and variables.

✅ **MCA Semester-1

Q301 – Q400 (100 Question–Answer Set)**

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Q301. What is a constant in C?

Ans: A value that cannot be changed during program execution.

Q302. Types of constants in C?

Ans: Integer, Float, Character, String, Symbolic.

Q303. What is a scope of a variable?

Ans: Region where a variable is accessible.

Q304. What is Local Variable?

Ans: Declared inside a function/block.

Q305. What is Global Variable?

Ans: Declared outside all functions.

Q306. What is Recursion?

Ans: Function calling itself.

Q307. Give example of recursive function.

Ans: Factorial, Fibonacci.

Q308. What is a structure padding?

Ans: Extra bytes added to align data in memory.

Q309. What is modular programming?

Ans: Dividing program into small modules/functions.

Q310. What is header file?

Ans: File containing function declarations and definitions (stdio.h, math.h).

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Q311. What is SQL?

Ans: Structured Query Language used for database operations.

Q312. Types of SQL commands?

Ans: DDL, DML, DCL, TCL, DQL.

Q313. What is DDL?

Ans: Data Definition Language (CREATE, ALTER).

Q314. What is DML?

Ans: Data Manipulation Language (INSERT, UPDATE).

Q315. What is DCL?

Ans: Data Control Language (GRANT, REVOKE).

Q316. What is TCL?

Ans: Transaction Control Language (COMMIT, ROLLBACK).

Q317. What is DQL?

Ans: Data Query Language (SELECT).

Q318. What is a JOIN?

Ans: Combines rows from multiple tables.

Q319. Types of JOINs?

Ans: INNER, LEFT, RIGHT, FULL.

Q320. What is an Index?

Ans: Increases speed of data retrieval.

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Q321. What is a process in OS?

Ans: A program in execution.

Q322. Process states?

Ans: New, Ready, Running, Blocked, Terminated.

Q323. What is a thread?

Ans: Smallest unit of CPU execution inside a process.

Q324. Difference: Process vs Thread?

Ans: Process = independent; Thread = lightweight, shares memory.

Q325. What is Race Condition?

Ans: When multiple processes access shared data concurrently.

Q326. What is Mutual Exclusion?

Ans: Ensures only one process accesses shared resource at a time.

Q327. What is Kernel?

Ans: Core of OS managing system resources.

Q328. Types of kernels?

Ans: Monolithic, Microkernel.

Q329. What is Booting?

Ans: Starting the computer and loading the OS.

Q330. What is File System?

Ans: Method for storing and organizing files.

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Q331. What is a Protocol?

Ans: Set of rules for data communication.

Q332. What is Circuit Switching?

Ans: Dedicated communication path (e.g., telephone).

Q333. What is Packet Switching?

Ans: Data broken into packets (e.g., internet).

Q334. What is Hub?

Ans: Basic device connecting multiple network devices; broadcasts data.

Q335. What is NIC?

Ans: Network Interface Card.

Q336. What is ARP?

Ans: Address Resolution Protocol – maps IP to MAC.

Q337. What is RARP?

Ans: Reverse ARP – maps MAC to IP.

Q338. What is Firewall?

Ans: Security system controlling network traffic.

Q339. What is Proxy Server?

Ans: Intermediate server between client and internet.

Q340. What is Latency?

Ans: Time delay in data transmission.

---

Q341. What is Cartesian Product?

Ans: Set of all ordered pairs (A × B).

Q342. What is a Matrix?

Ans: Arrangement of numbers in rows and columns.

Q343. Define Algorithm.

Ans: Step-by-step method to solve a problem.

Q344. What is Graph Isomorphism?

Ans: Two graphs with same structure.

Q345. What is Bipartite Graph?

Ans: Graph whose vertices can be divided into two sets.

Q346. What is Degree Sequence?

Ans: List of degrees of all vertices.

Q347. What is Combinatorics?

Ans: Study of counting and arrangements.

Q348. What is HCF?

Ans: Highest Common Factor.

Q349. What is LCM?

Ans: Lowest Common Multiple.

Q350. What is Recurrence Relation?

Ans: Defines sequence using previous terms.

---

Q351. What is pointer to pointer?

Ans: Double pointer storing address of another pointer.

Q352. What is dynamic memory allocation?

Ans: Allocating memory at runtime.

Q353. Give example of structure in C.

struct student { int id; char name[20]; };

Q354. What is union?

Ans: Data structure using shared memory location.

Q355. Difference between structure & union?

Ans: Structure = memory for each member; Union = shared memory.

Q356. What is enum?

Ans: User-defined type of named integer constants.

Q357. What is command line argument?

Ans: Passing values to program via terminal.

Q358. What is segmentation fault?

Ans: Invalid memory access.

Q359. What is macro expansion?

Ans: Replacing macro calls with definitions.

Q360. What is token in C?

Ans: Smallest element: keyword, identifier, constant, operator.

---

Q361. What is subquery in SQL?

Ans: Query inside another query.

Q362. What is correlated subquery?

Ans: Subquery dependent on outer query.

Q363. What is constraint?

Ans: Rule applied to table columns.

Q364. Types of constraints?

Ans: NOT NULL, CHECK, UNIQUE, PK, FK.

Q365. What is stored procedure?

Ans: Precompiled SQL code.

Q366. What is trigger?

Ans: Automatically executed block on events.

Q367. What is view?

Ans: Virtual table.

Q368. What is cursor?

Ans: Pointer used to traverse result rows.

Q369. What is composite attribute?

Ans: Attribute with multiple sub-components.

Q370. What is derived attribute?

Ans: Attribute computed from other attributes.

---

Q371. What is Inter-process Communication?

Ans: Mechanism for processes to communicate.

Q372. IPC methods?

Ans: Pipes, Message queues, Shared memory, Semaphores.

Q373. What is Memory Management?

Ans: OS process of allocating/deallocating memory.

Q374. What is Swapping?

Ans: Moving process between RAM and disk.

Q375. What is page fault?

Ans: Requested page not in memory.

Q376. What is Belady’s anomaly?

Ans: Page faults increase with more frames.

Q377. What is file descriptor?

Ans: Unique number ID for file access.

Q378. What is FAT?

Ans: File Allocation Table.

Q379. What is inode?

Ans: Metadata structure for files in UNIX.

Q380. What is Shell?

Ans: Interface between user and OS.

---

Q381. What is SSL?

Ans: Secure Sockets Layer for encrypted communication.

Q382. What is TLS?

Ans: Transport Layer Security — modern SSL version.

Q383. What is DHCP?

Ans: Dynamic Host Configuration Protocol — assigns IPs.

Q384. What is Gateway?

Ans: Connects different networks.

Q385. What is Bandwidth?

Ans: Maximum data transfer capacity.

Q386. What is Throughput?

Ans: Actual data transferred per time.

Q387. What is Ping?

Ans: Tests connection using ICMP.

Q388. What is VPN?

Ans: Secure private network over public internet.

Q389. What is Load Balancer?

Ans: Distributes network traffic among servers.

Q390. What is QoS?

Ans: Quality of Service for managing network traffic.

---

Q391. What is pigeonhole principle?

Ans: If n items in m boxes (n > m), at least one box contains 2 items.

Q392. What is Inclusion-Exclusion principle?

Ans: Helps count union of overlapping sets.

Q393. What is binary relation?

Ans: Relation between two sets.

Q394. What is adjacency matrix?

Ans: Matrix representation of a graph.

Q395. What is adjacency list?

Ans: List of connected vertices.

Q396. What is Euler path?

Ans: Covers every edge exactly once.

Q397. What is Hamiltonian path?

Ans: Covers every vertex exactly once.

Q398. What is logical equivalence?

Ans: Statements with same truth values.

Q399. What is quantifier?

Ans: ∀ (for all), ∃ (there exists).

Q400. What is combinatorial proof?

Ans: Proof using counting techniques.

✅ **MCA Semester-1

Q401 – Q500 (Final 100 Questions)**

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Q401. What is Bitwise AND operator?

Ans: Performs AND operation on each bit (&).

Q402. What is Bitwise OR operator?

Ans: Performs OR operation on each bit (|).

Q403. What is Bitwise XOR operator?

Ans: Performs exclusive OR (^).

Q404. What is Left Shift operator?

Ans: Shifts bits to left (<<).

Q405. What is Right Shift operator?

Ans: Shifts bits to right (>>).

Q406. What is typedef?

Ans: Creates new name for existing data type.

Q407. What is volatile keyword?

Ans: Prevents compiler from optimizing variable access.

Q408. What is static variable?

Ans: Retains value between function calls.

Q409. What is register variable?

Ans: Stored in CPU registers.

Q410. What is extern keyword?

Ans: Declares a global variable defined elsewhere.

---

Q411. What is ER Diagram?

Ans: Represents entities and their relationships.

Q412. What is Cardinality?

Ans: Defines relationship count (1:1, 1:M, M:N).

Q413. What is Primary Key?

Ans: Uniquely identifies a record.

Q414. What is Foreign Key?

Ans: Links two tables.

Q415. What is Surrogate Key?

Ans: Artificial key (auto-increment).

Q416. What is Composite Key?

Ans: Key made of multiple columns.

Q417. What is Normalization?

Ans: Removing redundancy and anomalies.

Q418. What are anomalies?

Ans: Update, Insert, Delete anomalies.

Q419. What is 1NF?

Ans: Atomic values, no repeating groups.

Q420. What is 2NF?

Ans: 1NF + no partial dependency.

---

Q421. What is 3NF?

Ans: 2NF + no transitive dependency.

Q422. What is BCNF?

Ans: Every determinant is a candidate key.

Q423. What is Denormalization?

Ans: Combining tables for faster queries.

Q424. Difference: Delete vs Truncate

Ans: DELETE = slow, logs; TRUNCATE = fast, no logs.

Q425. What is ACID property?

Ans: Atomicity, Consistency, Isolation, Durability.

Q426. What is Dirty Read?

Ans: Reading uncommitted changes.

Q427. What is Phantom Read?

Ans: New rows appear between queries.

Q428. What is Deadlock in DB?

Ans: Two processes waiting for each other.

Q429. What is BCNF violation?

Ans: When non-key attribute determines key.

Q430. What is OLAP?

Ans: Analytical processing (complex queries).

---

Q431. What is OLTP?

Ans: Transactional processing (fast inserts).

Q432. What is Data Warehouse?

Ans: Central repository of business data.

Q433. What is Data Mining?

Ans: Extracting patterns from data.

Q434. What is Star Schema?

Ans: Fact table with dimension tables.

Q435. What is Snowflake Schema?

Ans: Normalized star schema.

Q436. What is Scheduler? (OS)

Ans: Decides which process runs next.

Q437. Types of Scheduling?

Ans: FCFS, SJF, Priority, Round Robin.

Q438. What is Round Robin?

Ans: Each process runs for fixed time quantum.

Q439. What is Context Switching?

Ans: Saving CPU state during process switch.

Q440. What is Deadlock?

Ans: Two or more processes waiting for each other.

---

Q441. Deadlock conditions? (Coffman)

Ans: Mutual exclusion, Hold and wait, No preemption, Circular wait.

Q442. What is Semaphore?

Ans: Integer variable for synchronization.

Q443. Types of Semaphores?

Ans: Binary, Counting.

Q444. What is Starvation?

Ans: Process waits indefinitely.

Q445. What is Logical Address?

Ans: Generated by CPU.

Q446. What is Physical Address?

Ans: Actual location in memory.

Q447. What is Paging?

Ans: Dividing memory into fixed-size pages.

Q448. What is Segmentation?

Ans: Dividing memory into variable-size segments.

Q449. What is Thrashing?

Ans: Excessive paging causing slowdown.

Q450. What is DMA?

Ans: Direct Memory Access without CPU.

---

Q451. What is LAN?

Ans: Local network (small area).

Q452. What is MAN?

Ans: Metropolitan area network.

Q453. What is WAN?

Ans: Large area network (worldwide).

Q454. What is Router?

Ans: Forwards packets between networks.

Q455. What is Switch?

Ans: Connects devices using MAC addresses.

Q456. What is Bridge?

Ans: Connects LAN segments.

Q457. What is SMTP?

Ans: Email sending protocol.

Q458. What is POP3?

Ans: Email receiving protocol.

Q459. What is IMAP?

Ans: Email management protocol.

Q460. What is FTP?

Ans: File transfer protocol.

---

Q461. What is HTTP?

Ans: Web communication protocol.

Q462. What is HTTPS?

Ans: Secure HTTP using SSL/TLS.

Q463. What is IP?

Ans: Logical addressing protocol.

Q464. What is TCP?

Ans: Reliable, connection-oriented protocol.

Q465. What is UDP?

Ans: Fast, connectionless protocol.

Q466. What is DNS?

Ans: Converts domain to IP.

Q467. What is Subnet Mask?

Ans: Used to divide network into subnets.

Q468. What is IP Spoofing?

Ans: Forging IP identity.

Q469. What is Packet Sniffing?

Ans: Monitoring network traffic.

Q470. What is Encryption?

Ans: Convert data to unreadable form.

---

Q471. What is Decryption?

Ans: Converting encrypted data back.

Q472. What is Hashing?

Ans: One-way encryption creating fixed-size output.

Q473. What is Public Key?

Ans: Key used to encrypt message.

Q474. What is Private Key?

Ans: Key used to decrypt message.

Q475. What is SSH?

Ans: Secure remote login protocol.

Q476. What is Telnet?

Ans: Remote login without encryption.

Q477. What is VPN tunnel?

Ans: Encrypted path for secure data transfer.

Q478. What is Data Link Layer?

Ans: Provides framing and error detection.

Q479. What is Network Layer?

Ans: Handles routing and addressing.

Q480. What is Transport Layer?

Ans: Provides end-to-end communication.

---

Q481. What is Predicate Logic?

Ans: Logic using quantifiers and predicates.

Q482. What is Propositional Logic?

Ans: Logic using statements and operators.

Q483. What is Tautology?

Ans: Statement always true.

Q484. What is Contradiction?

Ans: Statement always false.

Q485. What is Contingency?

Ans: Can be true or false.

Q486. What is Set Partition?

Ans: Dividing set into disjoint subsets.

Q487. What is Function in mathematics?

Ans: Maps input to unique output.

Q488. What is Injective function?

Ans: One-to-one.

Q489. What is Surjective function?

Ans: Onto (covers entire codomain).

Q490. What is Bijective function?

Ans: One-to-one and onto.

---

Q491. What is Directed Graph?

Ans: Graph with directed edges.

Q492. What is Undirected Graph?

Ans: Graph with edges without direction.

Q493. What is Weighted Graph?

Ans: Graph with weighted edges.

Q494. What is Spanning Tree?

Ans: Tree covering all vertices.

Q495. What is MST?

Ans: Minimum Spanning Tree (Prim’s, Kruskal’s).

Q496. What is BFS?

Ans: Breadth-first search (level-wise).

Q497. What is DFS?

Ans: Depth-first search (stack).

Q498. What is Big-O notation?

Ans: Upper bound of algorithm complexity.

Q499. What is Pigeonhole proof?

Ans: Proof using pigeonhole principle.

Q500. What is Mathematical Induction?

Ans: Method to prove statements for all natural numbers.

🎓 MCA Semester-2 – Question & Answer Bank

✅ Unit-1: Data Structures (DS)

Q1–Q50

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Q1. What is a Data Structure?

Ans: A data structure is a way of organizing and storing data so that it can be accessed and used efficiently.

---

Q2. What are the types of data structures?

Ans:

1. Primitive: int, char, float

2. Non-Primitive:

   • Linear: Array, Linked List, Stack, Queue

   • Non-Linear: Tree, Graph

   • Hashing

---

Q3. What is an Array?

Ans: Array is a collection of similar data types stored in continuous memory locations.

---

Q4. Advantages of Arrays?

Ans:

• Fast access

• Easy to implement

• Memory efficient

---

Q5. Disadvantages of Arrays?

Ans:

• Fixed size

• Insertion/deletion is costly

---

Q6. What is a Linked List?

Ans: A linked list is a dynamic data structure where each element (node) contains:

1. Data

2. Pointer to next node

---

Q7. Types of Linked List?

Ans:

• Singly Linked List

• Doubly Linked List

• Circular Linked List

• Circular Doubly Linked List

---

Q8. What is a node?

Ans: Node is the basic unit of a linked list containing data and pointer.

---

Q9. What is Stack?

Ans: Stack is a linear data structure that follows LIFO – Last In First Out rule.

---

Q10. Applications of Stack?

Ans:

• Expression evaluation

• Undo/Redo

• Function calls

• Backtracking

---

Q11. What is Queue?

Ans: Queue is a linear data structure that follows FIFO – First In First Out rule.

---

Q12. Types of Queue?

Ans:

• Simple Queue

• Circular Queue

• Priority Queue

• Deque (Double Ended Queue)

---

Q13. What is Circular Queue?

Ans: A queue where last position is connected to first position to make a circle.

---

Q14. What is Tree?

Ans: Tree is a hierarchical data structure with nodes connected in parent-child form.

---

Q15. What is Binary Tree?

Ans: A tree where each node has at most 2 children.

---

Q16. What is Binary Search Tree (BST)?

Ans: A binary tree where:

• Left child < Root

• Right child > Root

---

Q17. What is Traversal?

Ans: Process of visiting each node of a tree.

---

Q18. Types of Traversal?

Ans:

1. Inorder

2. Preorder

3. Postorder

4. Level order

---

Q19. What is Graph?

Ans: Graph is a collection of nodes (vertices) and edges.

---

Q20. Types of Graph?

Ans:

• Directed

• Undirected

• Weighted

• Unweighted

---

Q21. BFS stands for?

Ans: Breadth First Search

---

Q22. DFS stands for?

Ans: Depth First Search

---

Q23. BFS uses which data structure?

Ans: Queue

---

Q24. DFS uses which data structure?

Ans: Stack / Recursion

---

Q25. What is Hashing?

Ans: Technique to map data to a fixed size table using a hash function.

---

Q26. What is a Hash Function?

Ans: Function that converts a key into an index of a hash table.

---

Q27. What is Collision?

Ans: When two keys generate the same hash index.

---

Q28. Collision resolution techniques?

Ans:

• Chaining

• Open Addressing

---

Q29. What is Algorithm?

Ans: A step-by-step process to solve a problem.

---

Q30. What is Time Complexity?

Ans: Time taken by an algorithm as input size grows.

---

Q31. What is Space Complexity?

Ans: Memory used by an algorithm.

---

Q32. Best case complexity of Binary Search?

Ans: O(1)

---

Q33. Worst case complexity of Binary Search?

Ans: O(log n)

---

Q34. Best case complexity of Linear Search?

Ans: O(1)

---

Q35. Worst case complexity of Linear Search?

Ans: O(n)

---

Q36. Bubble Sort complexity?

Ans:

• Best: O(n)

• Worst: O(n²)

---

Q37. Selection Sort complexity?

Ans: O(n²)

---

Q38. Insertion Sort complexity?

Ans:

• Best: O(n)

• Worst: O(n²)

---

Q39. Quick Sort complexity?

Ans:

• Best/Average: O(n log n)

• Worst: O(n²)

---

Q40. Merge Sort complexity?

Ans: O(n log n)

---

Q41. What is Recursion?

Ans: Function calling itself.

---

Q42. What is Base Case in recursion?

Ans: Condition at which recursion stops.

---

Q43. What is Dynamic Programming?

Ans: Technique of solving problems by storing previously computed results.

---

Q44. What is Greedy Algorithm?

Ans: Algorithm that makes the best choice at every step.

---

Q45. What is Stack Overflow?

Ans: Error when stack memory is full.

---

Q46. What is Queue Underflow?

Ans: Trying to delete element from empty queue.

---

Q47. What is Heap?

Ans: Complete binary tree used for priority queues.

---

Q48. Types of Heap?

Ans:

• Max Heap

• Min Heap

---

Q49. What is AVL Tree?

Ans: Self-balancing binary search tree.

---

Q50. What is B-Tree used for?

Ans: Database indexing and file systems.

🎓 MCA Semester-2 – Q51 to Q100

(Subject: Data Structures – Full Theory + Interview Level Concepts)

---

✅ Q51. What is Red-Black Tree?

Ans: A self-balancing binary search tree where each node has a color (red or black) and follows balancing rules.

---

Q52. Properties of Red-Black Tree?

Ans:

1. Every node is either red or black

2. Root is always black

3. No two consecutive red nodes

4. All leaf (NIL) nodes are black

5. Every path from a node to leaf contains same number of black nodes

---

Q53. What is Multi-way Tree?

Ans: A tree where nodes can have more than two children.

---

Q54. What is B+ Tree?

Ans: A tree where all data is stored only in leaf nodes; used in databases.

---

Q55. Difference between B-Tree and B+ Tree?

Ans:

• B-Tree: data in internal + leaf nodes

• B+ Tree: data only in leaf nodes → better searching

---

Q56. What is adjacency matrix?

Ans: A 2D matrix representation of a graph where 1 indicates edge.

---

Q57. What is adjacency list?

Ans: A list-based representation storing neighbors of each node.

---

Q58. Which is better: adjacency list or matrix?

Ans:

• Sparse graph → Adjacency List

• Dense graph → Adjacency Matrix

---

Q59. What is Topological Sorting?

Ans: Linear ordering of directed acyclic graph (DAG) nodes.

---

Q60. Applications of Topological Sort?

Ans:

• Task scheduling

• Job dependency

• Compiler optimization

---

Q61. What is Minimum Spanning Tree (MST)?

Ans: Subset of edges that connects all nodes with minimum cost.

---

Q62. MST algorithms?

Ans:

• Kruskal’s Algorithm

• Prim’s Algorithm

---

Q63. What is Dijkstra’s Algorithm?

Ans: Used to find shortest path from source to all nodes.

---

Q64. Dijkstra works only for?

Ans: Non-negative weights.

---

Q65. What is Bellman-Ford Algorithm?

Ans: Shortest path algorithm that works for negative weights.

---

Q66. Bellman-Ford detects what?

Ans: Negative weight cycles.

---

Q67. What is Floyd-Warshall Algorithm?

Ans: All-pairs shortest path algorithm.

---

Q68. What is Backtracking?

Ans: Trying different options and undoing (backtracking) on failure.

---

Q69. Example problems of backtracking?

Ans:

• N-Queens

• Sudoku

• Rat in a Maze

---

Q70. What is Divide and Conquer?

Ans: Breaking a problem into sub-problems → solving → combining.

---

Q71. Algorithms based on Divide and Conquer?

Ans:

• Merge Sort

• Quick Sort

• Binary Search

---

Q72. What is a Balanced Tree?

Ans: A tree where height difference is minimal for fast search.

---

Q73. What is Height of Tree?

Ans: Maximum number of edges from root to leaf.

---

Q74. What is Depth of Node?

Ans: Distance from root to that node.

---

Q75. What are Sparse Matrices?

Ans: Matrices with mostly zero values.

---

Q76. How to store Sparse Matrix efficiently?

Ans: Using Triplet Representation or Compressed Row Storage (CRS).

---

Q77. What is Priority Queue?

Ans: A queue where each element has priority; highest priority served first.

---

Q78. Priority Queue is implemented using?

Ans: Heap.

---

Q79. What is Linear Data Structure?

Ans: Data arranged sequentially (array, stack, queue).

---

Q80. What is Non-Linear Data Structure?

Ans: Data arranged hierarchically (tree, graph).

---

Q81. What is Amortized Analysis?

Ans: Average time taken per operation over multiple operations.

---

Q82. What is Deque?

Ans: Double-ended queue where insertion/deletion at both ends.

---

Q83. What is Circular Linked List?

Ans: Last node points back to the first node.

---

Q84. Advantage of Circular Linked List?

Ans:

• No NULL at end

• Easy to implement round-robin scheduling

---

Q85. What is Sentinel Node?

Ans: A dummy node used to simplify boundary conditions.

---

Q86. What is Threaded Binary Tree?

Ans: A binary tree where NULL pointers point to inorder predecessor/successor.

---

Q87. What is Hash Table?

Ans: A table storing key-value pairs using hashing.

---

Q88. What is Load Factor?

Ans:
Load factor = number of elements / table size

---

Q89. What is Rehashing?

Ans: Increasing table size and recalculating hash values when load factor increases.

---

Q90. What is Double Hashing?

Ans: Using two hash functions to resolve collisions.

---

Q91. What is Skip List?

Ans: A layered linked list for fast searching (O(log n)).

---

Q92. What is Treap?

Ans: Tree + Heap → Balanced BST using random priority.

---

Q93. What is Suffix Tree?

Ans: A compressed trie used for fast substring search.

---

Q94. What is Trie (Prefix Tree)?

Ans: A tree for string searching where each node stores characters.

---

Q95. What is Memoization?

Ans: Storing results of expensive function calls.

---

Q96. What is Greedy Choice Property?

Ans: A local best choice leads to global optimum.

---

Q97. What is Optimal Substructure?

Ans: Optimal solution contains optimal solutions of subproblems.

---

Q98. What is Queue Overflow?

Ans: Trying to insert when queue is full.

---

Q99. What is Expression Tree?

Ans: Binary tree used for evaluating expressions.

---

Q100. What is Postfix Expression?

Ans: Expression where operators appear after operands (like AB+).

🎓 MCA Semester-2 – Q101 to Q150

(DS + Algorithms full theory + interview-level concepts)

---

Q101. What is Prefix Expression?

Ans: Expression where operators are written before operands (e.g., +AB).

---

Q102. What is Infix Expression?

Ans: Normal expression where operators appear between operands (e.g., A + B).

---

Q103. Convert Infix to Postfix uses which DS?

Ans: Stack

---

Q104. What is ADT (Abstract Data Type)?

Ans: A specification of data + operations without internal implementation details.

---

Q105. Examples of ADT?

Ans:

• Stack

• Queue

• List

• Priority Queue

• Map

---

Q106. What is Linked List traversal?

Ans: Visiting each node from head to end.

---

Q107. What is a Tail Pointer?

Ans: Pointer that refers to the last node of a linked list.

---

Q108. What is a Self-Referential Structure?

Ans: A structure containing a pointer to another structure of same type.

---

Q109. What is Memory Fragmentation?

Ans: Broken memory blocks leading to inefficient memory usage.

---

Q110. What is Big-O notation?

Ans: Upper bound of an algorithm’s time/space complexity.

---

Q111. What is Omega notation?

Ans: Best-case time complexity.

---

Q112. What is Theta notation?

Ans: Average-case time complexity (tight bound).

---

Q113. Time complexity of stack operations?

Ans:

• Push → O(1)

• Pop → O(1)

---

Q114. Time complexity of queue operations?

Ans:

• Enqueue → O(1)

• Dequeue → O(1)

---

Q115. What is Overflow condition?

Ans: When inserting into a full DS (array/stack/queue).

---

Q116. What is Underflow condition?

Ans: When deleting from an empty DS.

---

Q117. Applications of Queue?

Ans:

• CPU scheduling

• Printers

• Ticket counters

• OS task management

---

Q118. Applications of Linked List?

Ans:

• Dynamic memory management

• Music/playlist management

• Hashing (chaining)

• File systems

---

Q119. Applications of Graphs?

Ans:

• Social networks

• Maps & navigation

• Networks

• Google search ranking

---

Q120. What is Weighted Graph?

Ans: Graph where edges have weights/costs.

---

Q121. What is Unweighted Graph?

Ans: Graph where edges have no weight.

---

Q122. What is Directed Graph?

Ans: Graph with directed edges (one-way).

---

Q123. What is Undirected Graph?

Ans: Graph with bidirectional edges.

---

Q124. What is a Complete Graph?

Ans: Graph where every node connects to every other node.

---

Q125. What is Degree of Node?

Ans: Number of edges connected to the node.

---

Q126. What is In-degree and Out-degree?

Ans:

• In-degree: number of incoming edges

• Out-degree: number of outgoing edges

---

Q127. What is Spanning Tree?

Ans: A tree connecting all nodes of a graph with minimum edges.

---

Q128. How many edges in spanning tree of N nodes?

Ans: N – 1

---

Q129. What is Articulation Point?

Ans: A node whose removal disconnects the graph.

---

Q130. What is Bridge (Cut-edge)?

Ans: An edge whose removal disconnects graph.

---

Q131. What is Strongly Connected Graph?

Ans: A directed graph where every node is reachable from every other node.

---

Q132. What is Weakly Connected Graph?

Ans: Directed graph becomes connected if directions are ignored.

---

Q133. What is DAG (Directed Acyclic Graph)?

Ans: Directed graph with no cycles.

---

Q134. DAG is used in?

Ans:

• Topological sorting

• Scheduling

• Compilers

---

Q135. What is Sorting?

Ans: Arranging elements in ascending or descending order.

---

Q136. What is Searching?

Ans: Finding an element in a collection.

---

Q137. Best sorting algorithm for large data?

Ans: Merge Sort (O(n log n)).

---

Q138. Which sorting is in-place?

Ans:

• Quick Sort

• Insertion Sort

• Selection Sort
  (not Merge Sort)

---

Q139. Which sorting is stable?

Ans:

• Merge Sort

• Bubble Sort

• Insertion Sort

---

Q140. What is Stable Sort?

Ans: Sorting where equal keys maintain original order.

---

Q141. What is Unstable Sort?

Ans: Sorting where equal keys may not preserve original order.

---

Q142. What is Heap Sort?

Ans: Sorting method using a heap data structure.

---

Q143. Heap Sort complexity?

Ans: O(n log n)

---

Q144. Quick Sort pivot selection?

Ans:

• First element

• Last element

• Middle

• Random pivot (best)

---

Q145. What is Randomized Algorithm?

Ans: Algorithm using random numbers to reduce worst-case chances.

---

Q146. What is Linear Probing?

Ans: Collision resolution by checking next slots sequentially.

---

Q147. What is Quadratic Probing?

Ans: Collision resolution by jumping squared distances (1², 2², 3²…).

---

Q148. What is Rehashing Frequency?

Ans: When load factor increases beyond threshold (0.7–0.8).

---

Q149. What is Multi-source BFS?

Ans: BFS starting from multiple nodes at once.

---

Q150. What is Multi-source Dijkstra?

Ans: Running Dijkstra from multiple starting nodes.

🎓 MCA Semester-2 – Q151 to Q200

---

Q151. What is Dynamic Memory Allocation?

Ans: Allocating memory at runtime using malloc(), calloc(), realloc() in C.

---

Q152. Difference between malloc() and calloc()?

Ans:

• malloc(n) → allocates n bytes, uninitialized

• calloc(n, size) → allocates n blocks of size bytes, initialized to 0

---

Q153. What is realloc()?

Ans: Resizes previously allocated memory block.

---

Q154. What is Memory Leak?

Ans: Memory that is allocated but never freed.

---

Q155. How to prevent memory leaks?

Ans: Using free() to deallocate memory when not needed.

---

Q156. What is Double Linked List?

Ans: Each node has data, next, and prev pointers.

---

Q157. Advantages of Doubly Linked List?

Ans:

• Traverse both directions

• Easy insertion/deletion in middle

---

Q158. What is Circular Doubly Linked List?

Ans: Last node points to first node, and first node’s prev points to last.

---

Q159. Applications of Linked List?

Ans:

• Implementation of stacks & queues

• Dynamic memory

• Polynomial arithmetic

• Adjacency list in graphs

---

Q160. What is Hashing Collision?

Ans: Two keys generate same hash index.

---

Q161. Hashing Techniques?

Ans:

• Chaining

• Open Addressing: Linear, Quadratic, Double Hashing

---

Q162. What is Separate Chaining?

Ans: Each hash table slot stores linked list of keys.

---

Q163. What is Open Addressing?

Ans: Collision resolved by probing alternate slots in the table.

---

Q164. What is Linear Probing?

Ans: Sequentially check next slot until empty found.

---

Q165. What is Quadratic Probing?

Ans: Check slots by adding square of step size.

---

Q166. What is Double Hashing?

Ans: Using two hash functions to reduce clustering.

---

Q167. What is Load Factor?

Ans: Load factor = n / table_size

---

Q168. When to Rehash?

Ans: When load factor exceeds threshold (e.g., 0.7–0.8).

---

Q169. What is Stack?

Ans: LIFO (Last In First Out) linear DS.

---

Q170. Applications of Stack?

Ans:

• Expression evaluation

• Function calls

• Undo/Redo

• Syntax parsing

---

Q171. Stack Implementation?

Ans:

• Array

• Linked List

---

Q172. Stack Overflow?

Ans: Pushing onto full stack.

---

Q173. Stack Underflow?

Ans: Popping from empty stack.

---

Q174. What is Queue?

Ans: FIFO (First In First Out) linear DS.

---

Q175. Types of Queue?

Ans:

• Simple Queue

• Circular Queue

• Priority Queue

• Deque

---

Q176. Circular Queue Advantage?

Ans: Efficient memory usage; no empty slots left after dequeue.

---

Q177. What is Deque?

Ans: Double-ended queue; insertion/deletion at both ends.

---

Q178. Priority Queue Implementation?

Ans: Using Heap (Min Heap or Max Heap).

---

Q179. Heap?

Ans: Complete binary tree used for priority queue.

---

Q180. Types of Heap?

Ans: Max Heap (root largest), Min Heap (root smallest)

---

Q181. What is Binary Tree?

Ans: Tree with at most 2 children per node.

---

Q182. Binary Tree Properties?

Ans:

• Max nodes at level l = 2^l

• Max nodes in tree of height h = 2^(h+1) – 1

---

Q183. What is Binary Search Tree (BST)?

Ans: Left child < root < right child

---

Q184. BST Operations?

Ans: Search, Insert, Delete, Traversal

---

Q185. Tree Traversal Methods?

Ans:

• Inorder

• Preorder

• Postorder

• Level Order

---

Q186. Recursive vs Iterative Traversal?

Ans: Recursive uses function call stack; Iterative uses explicit stack or queue.

---

Q187. What is AVL Tree?

Ans: Self-balancing BST; difference of left/right subtree heights ≤ 1.

---

Q188. AVL Tree Rotations?

Ans:

• Left Rotation

• Right Rotation

• Left-Right Rotation

• Right-Left Rotation

---

Q189. What is Red-Black Tree?

Ans: Self-balancing BST with node colors to maintain balance.

---

Q190. B-Tree Definition?

Ans: Multi-way search tree for databases; all leaves at same level.

---

Q191. B+ Tree Difference?

Ans: Internal nodes store only keys; data in leaf nodes; faster range queries.

---

Q192. Graph Definition?

Ans: Collection of vertices + edges.

---

Q193. Graph Types?

Ans:

• Directed / Undirected

• Weighted / Unweighted

• Cyclic / Acyclic

---

Q194. Graph Representation?

Ans:

• Adjacency Matrix

• Adjacency List

---

Q195. BFS Algorithm?

Ans: Level-order traversal using Queue.

---

Q196. DFS Algorithm?

Ans: Depth-first traversal using Stack / Recursion.

---

Q197. Topological Sorting?

Ans: Linear ordering of DAG nodes.

---

Q198. Applications of Graph?

Ans:

• Networking

• GPS / Maps

• Social Networks

• Scheduling

---

Q199. Shortest Path Algorithms?

Ans:

• Dijkstra (non-negative weights)

• Bellman-Ford (negative weights allowed)

• Floyd-Warshall (all-pairs)

---

Q200. Minimum Spanning Tree Algorithms?

Ans:

• Prim’s Algorithm

• Kruskal’s Algorithm

🎓 MCA Semester-2 – Q201 to Q250

---

Q201. What is Dynamic Programming (DP)?

Ans: Technique of solving problems by breaking into subproblems and storing results to avoid recomputation.

---

Q202. Difference between DP and Divide & Conquer?

Ans:

• DP stores results of subproblems

• Divide & Conquer recomputes subproblems

---

Q203. Types of DP?

Ans:

• Top-down (Memoization)

• Bottom-up (Tabulation)

---

Q204. What is Memoization?

Ans: Storing results of expensive function calls for future use.

---

Q205. What is Tabulation?

Ans: Solving DP iteratively and filling table.

---

Q206. Example problems of DP?

Ans:

• Fibonacci sequence

• Knapsack problem

• Longest Common Subsequence

• Matrix Chain Multiplication

---

Q207. What is Greedy Algorithm?

Ans: Algorithm making locally optimal choice at each step to find global optimum.

---

Q208. Difference between DP and Greedy?

Ans:

• DP considers all subproblems

• Greedy makes local optimal choice

---

Q209. Example of Greedy problem?

Ans:

• Activity selection

• Huffman coding

• Minimum Spanning Tree (Prim/Kruskal)

---

Q210. What is Backtracking?

Ans: Algorithmic technique to find solutions by trying all possibilities and abandoning if a solution fails.

---

Q211. Example problems of Backtracking?

Ans:

• N-Queens

• Sudoku solver

• Rat in a Maze

• Hamiltonian Path

---

Q212. What is Recursion?

Ans: Function calling itself directly or indirectly.

---

Q213. Components of recursion?

Ans:

• Base case

• Recursive case

---

Q214. Advantages of Recursion?

Ans:

• Simplifies code

• Useful in tree/graph traversal

• Solves divide & conquer problems easily

---

Q215. Disadvantages of Recursion?

Ans:

• High memory consumption

• Stack overflow

• Slower than iterative in some cases

---

Q216. What is Fibonacci sequence using DP?

Ans: Store previously computed Fibonacci numbers in array/table.

---

Q217. What is Longest Common Subsequence (LCS)?

Ans: Longest sequence common in given two sequences.

---

Q218. LCS Complexity?

Ans: O(m * n) using DP.

---

Q219. What is Longest Increasing Subsequence (LIS)?

Ans: Longest subsequence in which elements are sorted in increasing order.

---

Q220. LIS Complexity?

Ans: O(n²) standard DP; O(n log n) using binary search optimization.

---

Q221. What is Knapsack Problem?

Ans: Select items with given weight & value to maximize value within weight limit.

---

Q222. Types of Knapsack Problem?

Ans:

• 0/1 Knapsack

• Fractional Knapsack

---

Q223. 0/1 Knapsack solution?

Ans: Using DP table of size (number of items × capacity).

---

Q224. Fractional Knapsack solution?

Ans: Using Greedy Algorithm based on value/weight ratio.

---

Q225. What is Matrix Chain Multiplication?

Ans: Finding minimum cost of multiplying a sequence of matrices.

---

Q226. Matrix Chain Multiplication complexity?

Ans: O(n³) using DP.

---

Q227. What is Optimal Substructure?

Ans: Optimal solution contains optimal solutions of subproblems.

---

Q228. What is Overlapping Subproblems?

Ans: Subproblems recur multiple times in a recursive solution.

---

Q229. Difference between Recursion and DP?

Ans: DP avoids recomputation using memoization/tabulation.

---

Q230. What is Huffman Coding?

Ans: Greedy algorithm for data compression by variable-length prefix codes.

---

Q231. Huffman Coding Data Structure?

Ans: Priority Queue / Min Heap

---

Q232. What is Graph Traversal?

Ans: Visiting all nodes of a graph in systematic order.

---

Q233. BFS Algorithm?

Ans: Visit nodes level by level using Queue.

---

Q234. DFS Algorithm?

Ans: Visit nodes depth-wise using Stack / Recursion.

---

Q235. What is Topological Sort?

Ans: Linear ordering of vertices in a DAG.

---

Q236. Applications of Topological Sort?

Ans:

• Task scheduling

• Course prerequisite ordering

• Job sequencing

---

Q237. What is Minimum Spanning Tree (MST)?

Ans: Subset of edges connecting all vertices with minimum cost.

---

Q238. MST Algorithms?

Ans: Prim’s Algorithm, Kruskal’s Algorithm

---

Q239. Prim’s Algorithm?

Ans: Greedy algorithm starting from any node; adds minimum weight edge connecting tree to remaining vertices.

---

Q240. Kruskal’s Algorithm?

Ans: Greedy algorithm sorting all edges by weight and adding if no cycle is formed.

---

Q241. What is Cycle Detection in Graph?

Ans: Finding whether a graph contains a cycle.

---

Q242. Cycle Detection Algorithms?

Ans:

• DFS (back edges)

• Union-Find (Disjoint Set)

---

Q243. What is Disjoint Set?

Ans: Data structure to keep track of elements partitioned into sets.

---

Q244. Disjoint Set Operations?

Ans:

• Find → determine set of element

• Union → combine two sets

---

Q245. Disjoint Set Optimization?

Ans:

• Path Compression in Find

• Union by Rank

---

Q246. What is Dijkstra’s Algorithm?

Ans: Single-source shortest path for non-negative weighted graphs.

---

Q247. Bellman-Ford Algorithm?

Ans: Single-source shortest path; works with negative weights; detects negative cycles.

---

Q248. Floyd-Warshall Algorithm?

Ans: Computes shortest paths between all pairs of vertices; DP-based.

---

Q249. What is Multi-source BFS?

Ans: BFS starting from multiple nodes simultaneously.

---

Q250. Applications of Graph Algorithms?

Ans:

• Social network analysis

• Navigation & GPS

• Network routing

• Scheduling & dependency resolution

🎓 MCA Semester-2 – Q251 to Q300

---

Q251. What is Hamiltonian Path?

Ans: Path in a graph visiting each vertex exactly once.

---

Q252. What is Hamiltonian Cycle?

Ans: Hamiltonian path that starts and ends at the same vertex.

---

Q253. Difference between Eulerian and Hamiltonian?

Ans:

• Eulerian → visits all edges once

• Hamiltonian → visits all vertices once

---

Q254. What is Graph Coloring?

Ans: Assign colors to vertices such that no adjacent vertices have same color.

---

Q255. Application of Graph Coloring?

Ans:

• Scheduling problems

• Register allocation in compilers

• Map coloring

---

Q256. What is Minimum Vertex Cover?

Ans: Smallest set of vertices such that each edge has at least one endpoint in the set.

---

Q257. What is Maximum Matching?

Ans: Largest set of edges without common vertices.

---

Q258. What is Bipartite Graph?

Ans: Graph whose vertices can be divided into two sets such that edges connect only vertices from different sets.

---

Q259. How to check if a graph is bipartite?

Ans: Using BFS or DFS with 2-coloring.

---

Q260. What is Connected Graph?

Ans: Every pair of vertices has a path between them.

---

Q261. What is Strongly Connected Component (SCC)?

Ans: Maximal set of vertices in directed graph where each vertex reachable from every other vertex.

---

Q262. Algorithm for SCC?

Ans: Kosaraju’s or Tarjan’s Algorithm.

---

Q263. What is Shortest Path Problem?

Ans: Find minimum distance between nodes in weighted graph.

---

Q264. Single Source Shortest Path Algorithms?

Ans: Dijkstra, Bellman-Ford

---

Q265. All-Pairs Shortest Path Algorithm?

Ans: Floyd-Warshall

---

Q266. What is Adjacency Matrix?

Ans: 2D array representation of graph; 1 indicates edge presence.

---

Q267. What is Adjacency List?

Ans: Each vertex stores list of connected vertices.

---

Q268. Advantage of Adjacency List?

Ans: Memory efficient for sparse graphs.

---

Q269. Advantage of Adjacency Matrix?

Ans: Fast edge lookup (O(1)).

---

Q270. What is Sparse Graph?

Ans: Graph with relatively few edges compared to vertices.

---

Q271. What is Dense Graph?

Ans: Graph with close to maximum number of edges.

---

Q272. Graph Representation Comparison?

Ans:

• Sparse → Adjacency list

• Dense → Adjacency matrix

---

Q273. What is Weighted Graph?

Ans: Graph where edges have associated costs/weights.

---

Q274. Unweighted Graph?

Ans: All edges are equal; no weights.

---

Q275. Directed Acyclic Graph (DAG) Definition?

Ans: Directed graph with no cycles; used in topological sorting.

---

Q276. Applications of DAG?

Ans:

• Task scheduling

• Compilers

• Dependency resolution

---

Q277. What is Transitive Closure?

Ans: Graph where edge exists if a path exists between vertices.

---

Q278. Algorithm for Transitive Closure?

Ans: Floyd-Warshall

---

Q279. What is Prim’s Algorithm Steps?

Ans:

1. Start from any vertex

2. Pick minimum weight edge connecting tree to remaining vertex

3. Repeat until all vertices included

---

Q280. What is Kruskal’s Algorithm Steps?

Ans:

1. Sort all edges by weight

2. Add edge to MST if it does not form a cycle

3. Repeat until MST formed

---

Q281. Cycle Detection in Undirected Graph?

Ans: Using DFS or Union-Find (Disjoint Set)

---

Q282. Cycle Detection in Directed Graph?

Ans: Using DFS and checking back edges

---

Q283. What is Union-Find DS?

Ans: Tracks disjoint sets; supports Union and Find operations.

---

Q284. Path Compression in Union-Find?

Ans: Optimizes find by directly linking nodes to root.

---

Q285. Union by Rank?

Ans: Merge smaller tree under larger tree to keep it shallow.

---

Q286. What is Shortest Path in DAG?

Ans: Use topological sort followed by edge relaxation.

---

Q287. What is BFS Complexity?

Ans: O(V + E)

---

Q288. DFS Complexity?

Ans: O(V + E)

---

Q289. What is Topological Sort Complexity?

Ans: O(V + E)

---

Q290. What is MST Complexity?

Ans:

• Prim: O(E + V log V) using Min Heap

• Kruskal: O(E log E)

---

Q291. What is Graph Density?

Ans: Density = 2 * E / (V * (V-1)) for undirected graph

---

Q292. What is Graph Diameter?

Ans: Maximum shortest path length between any two vertices.

---

Q293. What is Graph Radius?

Ans: Minimum eccentricity among all vertices.

---

Q294. What is Eccentricity of Vertex?

Ans: Maximum distance from that vertex to any other vertex.

---

Q295. What is Degree of Vertex?

Ans: Number of edges connected to vertex.

---

Q296. In-degree and Out-degree?

Ans:

• In-degree → number of incoming edges

• Out-degree → number of outgoing edges

---

Q297. What is Weighted DAG?

Ans: DAG where edges have weights; used in scheduling.

---

Q298. Shortest Path in Weighted DAG?

Ans: Topological sort + relax edges in order.

---

Q299. What is Hamiltonian Path Complexity?

Ans: NP-complete

---

Q300. What is Hamiltonian Cycle Complexity?

Ans: NP-complete

🎓 MCA Semester-2 – Q301 to Q350

---

Q301. What is Fibonacci Heap?

Ans: A heap data structure supporting fast decrease-key and merge operations; used in advanced graph algorithms.

---

Q302. Fibonacci Heap Operations?

Ans:

• Insert → O(1) amortized

• Find-min → O(1)

• Extract-min → O(log n) amortized

• Decrease-key → O(1) amortized

• Merge → O(1)

---

Q303. What is Binomial Heap?

Ans: Heap implemented using a collection of binomial trees; supports fast merging.

---

Q304. Difference between Binomial and Fibonacci Heap?

Ans:

• Fibonacci heap has better amortized times for decrease-key

• Binomial heap has simpler structure

---

Q305. What is Sparse Table?

Ans: Preprocessing structure for range queries (min/max) in O(1) after O(n log n) preprocessing.

---

Q306. What is Segment Tree?

Ans: Tree data structure for efficient range queries and updates on arrays.

---

Q307. Segment Tree Complexity?

Ans:

• Build → O(n)

• Query → O(log n)

• Update → O(log n)

---

Q308. Difference between Fenwick Tree and Segment Tree?

Ans:

• Fenwick → simpler, only for cumulative operations

• Segment → supports range queries, range updates

---

Q309. What is Trie?

Ans: Tree-like data structure for storing strings, useful for prefix searching.

---

Q310. Applications of Trie?

Ans:

• Autocomplete

• Spell checker

• IP routing

---

Q311. What is Suffix Tree?

Ans: Compressed trie storing all suffixes of a string; used for substring search.

---

Q312. What is Suffix Array?

Ans: Sorted array of all suffixes of a string; memory efficient alternative to suffix tree.

---

Q313. What is KMP Algorithm?

Ans: Knuth-Morris-Pratt string matching algorithm; avoids re-comparing characters.

---

Q314. KMP Complexity?

Ans: O(n + m), where n = text length, m = pattern length.

---

Q315. What is Rabin-Karp Algorithm?

Ans: String matching using hashing of pattern and text substrings.

---

Q316. Rabin-Karp Complexity?

Ans:

• Best/Average → O(n + m)

• Worst → O(n*m) (hash collisions)

---

Q317. What is Z Algorithm?

Ans: Preprocesses string to compute Z-array for pattern matching in O(n) time.

---

Q318. What is Aho-Corasick Algorithm?

Ans: Multi-pattern string matching using Trie + failure links.

---

Q319. What is Rolling Hash?

Ans: Hash function allowing efficient computation of next substring hash using previous value.

---

Q320. What is Min Heap?

Ans: Complete binary tree where parent ≤ children; root = minimum element.

---

Q321. Max Heap?

Ans: Complete binary tree where parent ≥ children; root = maximum element.

---

Q322. Heap Applications?

Ans:

• Priority Queue

• Heap Sort

• Graph algorithms (Prim, Dijkstra)

---

Q323. Heapify?

Ans: Process of adjusting heap to satisfy heap property.

---

Q324. Heap Sort Steps?

Ans:

1. Build max heap

2. Swap root with last element

3. Reduce heap size and heapify

4. Repeat

---

Q325. Heap Sort Complexity?

Ans: O(n log n)

---

Q326. What is Balanced Binary Tree?

Ans: Tree with height difference ≤ 1 between left and right subtrees.

---

Q327. AVL Tree Definition?

Ans: Height-balanced BST; left and right subtree height difference ≤ 1.

---

Q328. AVL Tree Rotations?

Ans:

• Left rotation

• Right rotation

• Left-Right rotation

• Right-Left rotation

---

Q329. What is Red-Black Tree?

Ans: Self-balancing BST using node colors (red/black) to maintain balance.

---

Q330. Red-Black Tree Properties?

Ans:

1. Every node is red or black

2. Root is black

3. No consecutive red nodes

4. Equal black height in all paths

---

Q331. What is B-Tree?

Ans: Multi-way search tree; used in databases and file systems.

---

Q332. B+ Tree Difference?

Ans: Data stored only in leaf nodes; internal nodes store only keys.

---

Q333. B-Tree Insertion?

Ans: Insert key in correct node; split if node overflows; propagate split upwards.

---

Q334. B-Tree Deletion?

Ans: Remove key; merge or redistribute nodes if underflow occurs.

---

Q335. What is Graph?

Ans: Set of vertices + edges.

---

Q336. Graph Representation?

Ans:

• Adjacency Matrix

• Adjacency List

---

Q337. Directed vs Undirected Graph?

Ans:

• Directed → edges have direction

• Undirected → edges bidirectional

---

Q338. Weighted vs Unweighted Graph?

Ans:

• Weighted → edges have cost/weight

• Unweighted → all edges equal

---

Q339. Graph Traversal?

Ans: Visiting all vertices systematically: BFS or DFS.

---

Q340. BFS vs DFS?

Ans:

• BFS → level-wise, uses Queue

• DFS → depth-wise, uses Stack/Recursion

---

Q341. Shortest Path in Unweighted Graph?

Ans: Use BFS

---

Q342. Shortest Path in Weighted Graph?

Ans: Use Dijkstra (no negative weights) or Bellman-Ford (negative allowed)

---

Q343. All-Pairs Shortest Path?

Ans: Floyd-Warshall Algorithm

---

Q344. Minimum Spanning Tree (MST)?

Ans: Subset of edges connecting all vertices with minimum total weight.

---

Q345. MST Algorithms?

Ans: Prim’s Algorithm, Kruskal’s Algorithm

---

Q346. Applications of MST?

Ans:

• Network design

• Circuit design

• Approximation algorithms

---

Q347. Topological Sort?

Ans: Linear ordering of vertices in a DAG such that for every directed edge u→v, u comes before v.

---

Q348. Topological Sort Algorithms?

Ans:

• DFS-based

• Kahn’s Algorithm (BFS-based)

---

Q349. Hamiltonian Path?

Ans: Path visiting each vertex exactly once.

---

Q350. Hamiltonian Cycle?

Ans: Hamiltonian path that starts and ends at same vertex; NP-complete.

🎓 MCA Semester-2 – Q351 to Q400

---

Q351. What is NP-Complete Problem?

Ans: Problem for which no known polynomial-time solution exists, and solution can be verified in polynomial time.

---

Q352. Examples of NP-Complete Problems?

Ans:

• Hamiltonian Cycle

• Travelling Salesman Problem (TSP)

• 0/1 Knapsack

• Graph Coloring

---

Q353. What is NP-Hard Problem?

Ans: At least as hard as NP-Complete; may not be in NP (solution may not be verifiable in polynomial time).

---

Q354. Travelling Salesman Problem (TSP)?

Ans: Find shortest route visiting all cities exactly once and returning to start.

---

Q355. TSP Complexity?

Ans: NP-Hard

---

Q356. What is Approximation Algorithm?

Ans: Algorithm producing near-optimal solution in polynomial time.

---

Q357. Example of Approximation Algorithm?

Ans:

• MST-based TSP approximation

• Vertex cover approximation

---

Q358. What is Greedy Algorithm?

Ans: Algorithm making locally optimal choice to achieve global optimum.

---

Q359. Greedy Algorithm Problems?

Ans:

• Fractional Knapsack

• Huffman Coding

• Activity Selection

• Prim & Kruskal MST

---

Q360. Difference Between Greedy and DP?

Ans:

• Greedy → local optimum step → global optimum

• DP → considers all subproblems, memoization or tabulation

---

Q361. What is Backtracking?

Ans: Trial-and-error approach; abandons invalid paths; used for combinatorial problems.

---

Q362. Backtracking Problems?

Ans:

• N-Queens

• Rat in Maze

• Sudoku Solver

• Hamiltonian Path

---

Q363. What is Divide and Conquer?

Ans: Problem divided into smaller subproblems, solved recursively, then combined.

---

Q364. Divide & Conquer Examples?

Ans:

• Merge Sort

• Quick Sort

• Binary Search

• Matrix Multiplication

---

Q365. Quick Sort Complexity?

Ans:

• Best/Average → O(n log n)

• Worst → O(n²) (if pivot poor choice)

---

Q366. Merge Sort Complexity?

Ans: O(n log n) in all cases; stable sort.

---

Q367. Heap Sort Complexity?

Ans: O(n log n); not stable; in-place.

---

Q368. Linear Search Complexity?

Ans: O(n)

---

Q369. Binary Search Complexity?

Ans: O(log n); requires sorted array.

---

Q370. Interpolation Search?

Ans: Search assuming uniform distribution; complexity: O(log log n) best case.

---

Q371. Exponential Search?

Ans: Finds range with powers of 2, then binary search; O(log n)

---

Q372. Jump Search?

Ans: Block search for sorted array; O(√n)

---

Q373. What is Amortized Analysis?

Ans: Average time per operation over a sequence of operations.

---

Q374. Amortized Analysis Example?

Ans: Dynamic array resizing; stack push/pop; splay trees

---

Q375. What is Bloom Filter?

Ans: Probabilistic data structure for set membership; allows false positives but no false negatives.

---

Q376. Applications of Bloom Filter?

Ans:

• Caches

• Databases

• Spell checkers

• Network routing

---

Q377. What is Skip List?

Ans: Layered linked list supporting fast search, insert, delete in O(log n).

---

Q378. Skip List vs Balanced Tree?

Ans:

• Skip list simpler to implement

• Balanced tree (AVL/Red-Black) deterministic height

---

Q379. What is Disjoint Set Union (DSU)?

Ans: Maintains disjoint sets; supports union and find operations efficiently.

---

Q380. DSU Applications?

Ans:

• Kruskal’s MST

• Network connectivity

• Detect cycles in graph

---

Q381. What is Path Compression?

Ans: Optimizes DSU’s find operation by linking nodes directly to root.

---

Q382. Union by Rank?

Ans: Attach smaller tree under larger tree to keep depth minimal.

---

Q383. What is Segment Tree?

Ans: Tree for range queries & updates on array.

---

Q384. Segment Tree Applications?

Ans:

• Range sum

• Range min/max

• Interval queries

---

Q385. Fenwick Tree / Binary Indexed Tree?

Ans: Data structure for cumulative frequency/range queries.

---

Q386. Fenwick Tree Complexity?

Ans:

• Query → O(log n)

• Update → O(log n)

---

Q387. Trie Applications?

Ans:

• Autocomplete

• Dictionary lookup

• IP routing

---

Q388. Suffix Tree Applications?

Ans:

• Pattern matching

• Substring search

• Longest repeated substring

---

Q389. Rabin-Karp Algorithm?

Ans: String matching using hashing; good for multiple patterns.

---

Q390. KMP Algorithm?

Ans: Pattern matching using LPS array to avoid recomputation; O(n+m)

---

Q391. Z-Algorithm?

Ans: Linear-time pattern matching using Z-array; O(n+m)

---

Q392. Aho-Corasick Algorithm?

Ans: Multi-pattern matching using Trie + failure links.

---

Q393. What is Rolling Hash?

Ans: Computes next substring hash using previous hash; efficient in Rabin-Karp.

---

Q394. What is BFS Complexity?

Ans: O(V + E)

---

Q395. DFS Complexity?

Ans: O(V + E)

---

Q396. Topological Sort Complexity?

Ans: O(V + E)

---

Q397. Dijkstra Complexity?

Ans:

• Using Min Heap → O(E + V log V)

---

Q398. Bellman-Ford Complexity?

Ans: O(V × E)

---

Q399. Floyd-Warshall Complexity?

Ans: O(V³)

---

Q400. Prim & Kruskal Complexity?

Ans:

• Prim → O(E + V log V) using heap

• Kruskal → O(E log E)

🎓 MCA Semester-2 – Q401 to Q450

---

Q401. What is Activity Selection Problem?

Ans: Select maximum number of non-overlapping activities; solved using Greedy algorithm.

---

Q402. Greedy Choice Property?

Ans: Local optimum leads to global optimum.

---

Q403. Optimal Substructure Property?

Ans: Problem’s optimal solution can be constructed from subproblems’ solutions.

---

Q404. Fractional Knapsack Problem?

Ans: Take fraction of items to maximize value; solved using Greedy.

---

Q405. 0/1 Knapsack Problem?

Ans: Items can’t be divided; solved using Dynamic Programming.

---

Q406. Job Scheduling Problem?

Ans: Assign jobs with deadlines and profits to maximize total profit; Greedy approach used.

---

Q407. Huffman Coding Algorithm?

Ans: Greedy algorithm for data compression; uses Min Heap to build prefix tree.

---

Q408. Graph Representation Comparison?

Ans:

• Adjacency Matrix → fast edge lookup, more memory

• Adjacency List → memory efficient, slower lookup

---

Q409. BFS Applications?

Ans:

• Shortest path in unweighted graphs

• Level order traversal

• Web crawlers

---

Q410. DFS Applications?

Ans:

• Detect cycles

• Topological sort

• Maze solving

• Connectivity checks

---

Q411. Topological Sort Applications?

Ans:

• Task scheduling

• Prerequisite ordering

• Build system dependencies

---

Q412. Single Source Shortest Path Problem?

Ans: Find shortest path from a source vertex to all other vertices; use Dijkstra/Bellman-Ford.

---

Q413. All-Pairs Shortest Path Problem?

Ans: Find shortest paths between every pair of vertices; use Floyd-Warshall.

---

Q414. MST Problem Definition?

Ans: Minimum set of edges connecting all vertices with minimum total weight.

---

Q415. Prim’s Algorithm Steps?

Ans:

1. Pick any vertex

2. Add edge with minimum weight connecting to tree

3. Repeat until all vertices included

---

Q416. Kruskal’s Algorithm Steps?

Ans:

1. Sort all edges by weight

2. Add edge if it doesn’t form cycle (using DSU)

3. Repeat until MST formed

---

Q417. Graph Cycle Detection in Undirected Graph?

Ans: Using DFS or Union-Find.

---

Q418. Cycle Detection in Directed Graph?

Ans: Using DFS and checking for back edges.

---

Q419. Hamiltonian Path Problem?

Ans: Path visiting each vertex exactly once; NP-Complete.

---

Q420. Hamiltonian Cycle Problem?

Ans: Hamiltonian path returning to start; NP-Complete.

---

Q421. Travelling Salesman Problem (TSP)?

Ans: Shortest tour visiting all cities exactly once; NP-Hard.

---

Q422. Approximation Algorithm for TSP?

Ans: Use MST-based heuristic for near-optimal solution.

---

Q423. Bellman-Ford Algorithm Steps?

Ans:

1. Initialize distances

2. Relax all edges V-1 times

3. Check for negative cycles

---

Q424. Dijkstra Algorithm Steps?

Ans:

1. Initialize distances

2. Pick vertex with minimum distance

3. Relax adjacent edges

4. Repeat until all vertices processed

---

Q425. Floyd-Warshall Algorithm Steps?

Ans: Dynamic programming to compute shortest paths for all vertex pairs.

---

Q426. What is Disjoint Set Union (DSU)?

Ans: Data structure to track disjoint sets; supports Union and Find operations.

---

Q427. DSU Applications?

Ans:

• Kruskal’s MST

• Cycle detection

• Connectivity queries

---

Q428. Path Compression in DSU?

Ans: Optimize Find by linking nodes directly to root.

---

Q429. Union by Rank in DSU?

Ans: Attach smaller tree under larger tree to keep depth minimal.

---

Q430. Segment Tree Definition?

Ans: Tree structure for efficient range queries and updates on arrays.

---

Q431. Segment Tree Applications?

Ans:

• Range sum

• Range min/max

• Interval queries

---

Q432. Fenwick Tree (Binary Indexed Tree)?

Ans: Efficient for cumulative frequency and prefix sum queries.

---

Q433. Fenwick Tree Complexity?

Ans: O(log n) for both query and update.

---

Q434. Trie Data Structure?

Ans: Tree for storing strings; supports prefix search efficiently.

---

Q435. Trie Applications?

Ans:

• Autocomplete

• Spell checker

• IP routing

---

Q436. Suffix Tree Definition?

Ans: Compressed Trie storing all suffixes of a string.

---

Q437. Suffix Tree Applications?

Ans:

• Pattern matching

• Longest repeated substring

• Text indexing

---

Q438. KMP Algorithm Steps?

Ans:

1. Preprocess pattern to compute LPS array

2. Match pattern using LPS to skip unnecessary comparisons

---

Q439. KMP Complexity?

Ans: O(n + m), n = text length, m = pattern length.

---

Q440. Rabin-Karp Algorithm Steps?

Ans:

1. Compute hash of pattern

2. Compute rolling hash of text substrings

3. Compare hashes; verify actual string if hashes match

---

Q441. Rabin-Karp Complexity?

Ans:

• Best/Average → O(n + m)

• Worst → O(n*m) (hash collisions)

---

Q442. Z-Algorithm for Pattern Matching?

Ans: Preprocess string to compute Z-array; O(n + m) time.

---

Q443. Aho-Corasick Algorithm?

Ans: Multi-pattern string matching using Trie + failure links; O(n + m + z).

---

Q444. Rolling Hash Definition?

Ans: Compute next substring hash using previous value; used in Rabin-Karp.

---

Q445. Heap Definition?

Ans: Complete binary tree with heap property: Max-Heap or Min-Heap.

---

Q446. Heap Applications?

Ans:

• Priority Queue

• Heap Sort

• Graph algorithms (Prim/Dijkstra)

---

Q447. Heap Operations?

Ans: Insert, Extract-Min/Max, Heapify, Decrease-Key

---

Q448. Heap Sort Steps?

Ans:

1. Build Max Heap

2. Swap root with last element

3. Reduce heap size, heapify

4. Repeat

---

Q449. Heap Sort Complexity?

Ans: O(n log n); not stable; in-place.

---

Q450. Balanced Binary Tree Definition?

Ans: Height difference between left and right subtrees ≤ 1; ensures O(log n) operations.

🎓 MCA Semester-2 – Q451 to Q500

---

Q451. AVL Tree Definition?

Ans: Self-balancing binary search tree; height difference ≤ 1 between left and right subtrees.

---

Q452. AVL Tree Rotations?

Ans:

• Single Rotation: Left, Right

• Double Rotation: Left-Right, Right-Left

---

Q453. AVL Tree Insertion?

Ans: Insert node like BST; rebalance tree using rotations if needed.

---

Q454. AVL Tree Deletion?

Ans: Delete node like BST; rebalance tree using rotations if needed.

---

Q455. Red-Black Tree Definition?

Ans: Self-balancing BST using node colors (red/black) to maintain balance.

---

Q456. Red-Black Tree Properties?

Ans:

1. Node is red or black

2. Root is black

3. No consecutive red nodes

4. All paths from node to leaves have same black height

---

Q457. B-Tree Definition?

Ans: Multi-way search tree used in databases and file systems; all leaves at same level.

---

Q458. B-Tree Insertion Steps?

Ans: Insert in proper node; if overflow, split node and propagate up.

---

Q459. B-Tree Deletion Steps?

Ans: Delete key; merge or redistribute nodes if underflow occurs.

---

Q460. B+ Tree Difference?

Ans:

• Internal nodes store only keys

• All data in leaf nodes

• Faster range queries

---

Q461. Binary Search Tree (BST)?

Ans: Left child < root < right child; supports efficient search, insert, delete.

---

Q462. BST Operations Complexity?

Ans:

• Search, Insert, Delete → O(h), h = tree height

• Balanced tree → O(log n)

---

Q463. Graph Definition?

Ans: Collection of vertices and edges representing relationships.

---

Q464. Directed vs Undirected Graph?

Ans:

• Directed → edges have direction

• Undirected → edges bidirectional

---

Q465. Weighted vs Unweighted Graph?

Ans:

• Weighted → edges have cost/weight

• Unweighted → all edges equal

---

Q466. Sparse vs Dense Graph?

Ans:

• Sparse → few edges (use adjacency list)

• Dense → many edges (use adjacency matrix)

---

Q467. Graph Representation?

Ans:

• Adjacency List → memory efficient for sparse graphs

• Adjacency Matrix → fast edge lookup

---

Q468. BFS Algorithm?

Ans: Visit nodes level-wise using queue; O(V + E) complexity.

---

Q469. DFS Algorithm?

Ans: Visit nodes depth-wise using recursion/stack; O(V + E) complexity.

---

Q470. Topological Sort Algorithm?

Ans:

• DFS-based or Kahn’s Algorithm

• Linear ordering of DAG vertices

---

Q471. Single Source Shortest Path?

Ans: Dijkstra for non-negative edges; Bellman-Ford for negative edges.

---

Q472. All-Pairs Shortest Path?

Ans: Floyd-Warshall Algorithm; O(V³) complexity.

---

Q473. Minimum Spanning Tree (MST)?

Ans: Subset of edges connecting all vertices with minimum weight.

---

Q474. Prim’s Algorithm Steps?

Ans: Start with vertex; add minimum weight edge to tree until all vertices included.

---

Q475. Kruskal’s Algorithm Steps?

Ans: Sort edges; add to MST if no cycle formed using DSU.

---

Q476. Cycle Detection in Graph?

Ans:

• Undirected → DFS / Union-Find

• Directed → DFS with back edges

---

Q477. Hamiltonian Path & Cycle?

Ans: NP-Complete problems; path visits all vertices; cycle returns to start.

---

Q478. Travelling Salesman Problem (TSP)?

Ans: Shortest route visiting all cities; NP-Hard.

---

Q479. Approximation Algorithms?

Ans: Provide near-optimal solution in polynomial time (e.g., MST-based TSP).

---

Q480. Dynamic Programming (DP)?

Ans: Solve problem by breaking into subproblems and storing results.

---

Q481. DP Techniques?

Ans:

• Top-Down (Memoization)

• Bottom-Up (Tabulation)

---

Q482. DP Example Problems?

Ans:

• Fibonacci Sequence

• 0/1 Knapsack

• LCS

• Matrix Chain Multiplication

---

Q483. Greedy Algorithm Definition?

Ans: Makes local optimal choice at each step to achieve global optimum.

---

Q484. Greedy Problem Examples?

Ans: Fractional Knapsack, Activity Selection, Huffman Coding, MST.

---

Q485. Backtracking Algorithm?

Ans: Tries all possibilities; abandons invalid paths; used for combinatorial problems.

---

Q486. Backtracking Problems?

Ans: N-Queens, Sudoku, Rat in Maze, Hamiltonian Path.

---

Q487. Divide & Conquer Algorithm?

Ans: Divide problem into subproblems; solve recursively; combine results.

---

Q488. Divide & Conquer Examples?

Ans: Merge Sort, Quick Sort, Binary Search, Matrix Multiplication.

---

Q489. String Matching Algorithms?

Ans: KMP, Rabin-Karp, Z-Algorithm, Aho-Corasick.

---

Q490. KMP Algorithm?

Ans: Uses LPS array to avoid unnecessary comparisons; O(n + m).

---

Q491. Rabin-Karp Algorithm?

Ans: Uses rolling hash for efficient pattern matching; handles multiple patterns.

---

Q492. Z-Algorithm?

Ans: Linear time string matching using Z-array; O(n + m).

---

Q493. Aho-Corasick Algorithm?

Ans: Multi-pattern search using Trie + failure links; O(n + m + z).

---

Q494. Rolling Hash Concept?

Ans: Efficiently compute next substring hash from previous hash.

---

Q495. Heap Definition?

Ans: Complete binary tree maintaining heap property; Max or Min heap.

---

Q496. Heap Applications?

Ans: Priority Queue, Heap Sort, Graph Algorithms (Prim/Dijkstra).

---

Q497. Heap Operations?

Ans: Insert, Extract-Min/Max, Heapify, Decrease-Key.

---

Q498. Heap Sort Steps?

Ans: Build max heap; swap root with last; reduce size and heapify; repeat.

---

Q499. Heap Sort Complexity?

Ans: O(n log n); in-place; not stable.

---

Q500. Balanced Binary Tree Definition?

Ans: Tree where height difference between left and right subtrees ≤ 1; ensures O(log n) operations.

🎓 MCA Semester-3 – Q1 to Q50

---

Q1. What is Database Management System (DBMS)?

Ans: Software for managing, storing, and retrieving data efficiently in structured format.

---

Q2. Types of DBMS?

Ans:

• Hierarchical

• Network

• Relational

• Object-Oriented

---

Q3. What is RDBMS?

Ans: Relational Database Management System; stores data in tables (rows & columns).

---

Q4. Keys in RDBMS?

Ans:

• Primary Key

• Foreign Key

• Candidate Key

• Composite Key

• Super Key

---

Q5. What is Normalization?

Ans: Process to remove redundancy and dependency by dividing tables into smaller tables.

---

Q6. Normal Forms?

Ans:

• 1NF → eliminate repeating groups

• 2NF → remove partial dependency

• 3NF → remove transitive dependency

• BCNF → stricter 3NF

---

Q7. Denormalization?

Ans: Combining tables to reduce joins and improve query performance.

---

Q8. SQL vs NoSQL?

Ans:

• SQL → Structured, Relational

• NoSQL → Non-Relational, Flexible schema

---

Q9. What is Transaction in DBMS?

Ans: Sequence of operations performed as a single logical unit.

---

Q10. ACID Properties?

Ans:

• Atomicity → All or nothing

• Consistency → Database remains consistent

• Isolation → Transactions do not interfere

• Durability → Permanent changes

---

Q11. Concurrency Control?

Ans: Managing simultaneous execution of transactions to maintain data integrity.

---

Q12. Deadlock in DBMS?

Ans: Situation where two or more transactions wait indefinitely for each other’s resources.

---

Q13. Deadlock Prevention?

Ans: Assign priorities, request ordering, or use resource allocation protocols.

---

Q14. Deadlock Detection?

Ans: Maintain wait-for graph and detect cycles.

---

Q15. Indexing in DBMS?

Ans: Data structure to improve query performance (e.g., B-Tree, Hash index).

---

Q16. Clustered vs Non-Clustered Index?

Ans:

• Clustered → physically sorts data

• Non-Clustered → separate structure pointing to rows

---

Q17. Stored Procedure?

Ans: Precompiled SQL statements stored in DB for repeated use.

---

Q18. Trigger in DBMS?

Ans: Automatically executed action when a specified event occurs.

---

Q19. View in DBMS?

Ans: Virtual table derived from one or more tables; does not store data physically.

---

Q20. Materialized View?

Ans: View that stores the query result physically for faster access.

---

Q21. What is Operating System (OS)?

Ans: Software managing hardware, software resources, and providing services to programs.

---

Q22. Types of OS?

Ans:

• Batch

• Time-Sharing

• Distributed

• Real-Time

---

Q23. Process vs Thread?

Ans:

• Process → independent program execution unit

• Thread → lightweight process sharing memory with parent

---

Q24. Multithreading Advantages?

Ans:

• Efficient CPU utilization

• Faster execution

• Shared memory

---

Q25. Process Scheduling?

Ans: Deciding which process gets CPU and in what order.

---

Q26. Scheduling Algorithms?

Ans:

• FCFS → First Come First Serve

• SJF → Shortest Job First

• Round Robin

• Priority Scheduling

---

Q27. Deadlock in OS?

Ans: Processes wait indefinitely for resources held by each other.

---

Q28. Deadlock Prevention & Avoidance?

Ans:

• Prevention → prevent one of 4 conditions (Mutual exclusion, Hold & Wait, No preemption, Circular wait)

• Avoidance → Banker's Algorithm

---

Q29. Virtual Memory?

Ans: Technique to use disk as an extension of RAM; enables large address space.

---

Q30. Paging vs Segmentation?

Ans:

• Paging → Fixed-size blocks (pages)

• Segmentation → Logical divisions of variable size

---

Q31. Page Replacement Algorithms?

Ans:

• FIFO → First In First Out

• LRU → Least Recently Used

• Optimal → Replace page not used for longest time

---

Q32. Thrashing in OS?

Ans: Excessive paging causing low CPU utilization.

---

Q33. Software Engineering Definition?

Ans: Systematic approach to design, develop, test, and maintain software.

---

Q34. SDLC Phases?

Ans:

1. Requirement Analysis

2. Design

3. Implementation

4. Testing

5. Deployment

6. Maintenance

---

Q35. Software Development Models?

Ans:

• Waterfall

• Agile

• Spiral

• V-Model

• RAD

---

Q36. Agile Methodology?

Ans: Iterative development with collaboration, flexibility, and fast delivery.

---

Q37. Scrum Roles?

Ans: Product Owner, Scrum Master, Development Team

---

Q38. Cloud Computing Definition?

Ans: Deliver computing services (servers, storage, DB, software) over the internet.

---

Q39. Cloud Service Models?

Ans:

• IaaS → Infrastructure as a Service

• PaaS → Platform as a Service

• SaaS → Software as a Service

---

Q40. Cloud Deployment Models?

Ans:

• Public Cloud

• Private Cloud

• Hybrid Cloud

• Community Cloud

---

Q41. Big Data Definition?

Ans: Large datasets that cannot be processed by traditional methods; characterized by 5Vs: Volume, Velocity, Variety, Veracity, Value.

---

Q42. Hadoop Framework?

Ans: Open-source framework for distributed storage and processing of big data.

---

Q43. Hadoop Components?

Ans:

• HDFS → Distributed storage

• MapReduce → Parallel processing

• YARN → Resource management

---

Q44. MapReduce Phases?

Ans:

1. Map → processes input data and generates key-value pairs

2. Reduce → aggregates results

---

Q45. HDFS Features?

Ans:

• Fault tolerant

• Distributed storage

• High throughput

---

Q46. NoSQL Databases?

Ans: Non-relational DB; supports unstructured data, horizontal scaling.

---

Q47. Types of NoSQL DB?

Ans:

• Document Store → MongoDB

• Key-Value → Redis

• Column Store → Cassandra

• Graph DB → Neo4j

---

Q48. CAP Theorem?

Ans: Consistency, Availability, Partition Tolerance – can only have 2/3 in distributed system.

---

Q49. Data Warehouse Definition?

Ans: Central repository for integrated data from multiple sources; used for analytics.

---

Q50. OLTP vs OLAP?

Ans:

• OLTP → Transactional, frequent inserts/updates

• OLAP → Analytical, complex queries

🎓 MCA Semester-3 – Q51 to Q100

---

Q51. Data Mining Definition?

Ans: Extracting useful patterns, trends, and knowledge from large datasets.

---

Q52. Data Mining Techniques?

Ans:

• Classification

• Clustering

• Association Rule Mining

• Regression

---

Q53. Classification in Data Mining?

Ans: Assigning items to predefined categories using algorithms like Decision Trees, Naive Bayes.

---

Q54. Clustering in Data Mining?

Ans: Grouping similar data points without predefined labels (e.g., K-Means).

---

Q55. Association Rule Mining?

Ans: Discovering interesting relationships among variables (e.g., Market Basket Analysis).

---

Q56. Apriori Algorithm?

Ans: Frequent itemset generation and association rule mining in transactional datasets.

---

Q57. Decision Tree?

Ans: Tree structure used for classification and regression.

---

Q58. ID3 Algorithm?

Ans: Decision tree algorithm using Information Gain to select attributes.

---

Q59. Random Forest?

Ans: Ensemble of decision trees; improves accuracy and reduces overfitting.

---

Q60. Support Vector Machine (SVM)?

Ans: Supervised ML algorithm; finds hyperplane separating classes with maximum margin.

---

Q61. Big Data Analytics?

Ans: Analyzing large, complex datasets to uncover patterns and insights.

---

Q62. Hadoop vs Spark?

Ans:

• Hadoop → Batch processing; disk-based; slower

• Spark → In-memory processing; fast; supports batch & real-time

---

Q63. MapReduce Job Components?

Ans:

• Mapper → processes input

• Reducer → aggregates output

• Driver → orchestrates job

---

Q64. HDFS Block Size?

Ans: Default 128MB per block (can be configured).

---

Q65. NameNode & DataNode?

Ans:

• NameNode → manages metadata, file system namespace

• DataNode → stores actual data blocks

---

Q66. YARN in Hadoop?

Ans: Resource manager for job scheduling and cluster resource allocation.

---

Q67. Cloud Computing Advantages?

Ans:

• Cost-efficient

• Scalable

• Flexible access

• High availability

---

Q68. Cloud Computing Disadvantages?

Ans:

• Security concerns

• Downtime risks

• Dependency on internet

---

Q69. SaaS Examples?

Ans: Google Workspace, Salesforce, Zoom.

---

Q70. PaaS Examples?

Ans: Heroku, Google App Engine, Microsoft Azure App Services.

---

Q71. IaaS Examples?

Ans: AWS EC2, Google Compute Engine, Microsoft Azure VMs.

---

Q72. Load Balancing in Cloud?

Ans: Distributing workloads across multiple servers to improve performance and availability.

---

Q73. Virtualization in Cloud?

Ans: Creating virtual instances of hardware resources; enables efficient resource utilization.

---

Q74. Multi-Tenancy in Cloud?

Ans: Single instance of software serving multiple customers with data isolation.

---

Q75. Cloud Security Measures?

Ans:

• Encryption

• Authentication & Authorization

• Firewall & IDS

• Backup & Disaster Recovery

---

Q76. NoSQL vs SQL for Big Data?

Ans:

• NoSQL → Handles unstructured/ semi-structured data; scalable

• SQL → Structured data; ACID compliant

---

Q77. CAP Theorem Explanation?

Ans: Distributed system can guarantee only 2 of 3: Consistency, Availability, Partition Tolerance.

---

Q78. Hadoop Ecosystem Components?

Ans:

• HDFS → Storage

• MapReduce → Processing

• Hive → SQL-like queries

• Pig → Script-based processing

• HBase → NoSQL DB

• Sqoop/Flume → Data ingestion

---

Q79. Hive vs Pig?

Ans:

• Hive → SQL-like queries, good for analysts

• Pig → Script-based, good for programmers

---

Q80. HBase Features?

Ans:

• Column-oriented

• NoSQL

• Real-time read/write

• Scalable

---

Q81. OLAP Operations?

Ans:

• Roll-up

• Drill-down

• Slice

• Dice

• Pivot

---

Q82. Data Warehouse vs Database?

Ans:

• Data Warehouse → For analytics, historical data

• Database → For transactional operations

---

Q83. Cloud Storage Services?

Ans: AWS S3, Google Cloud Storage, Azure Blob Storage

---

Q84. Edge Computing?

Ans: Processing data near data source to reduce latency.

---

Q85. Fog Computing?

Ans: Extension of cloud to the edge; intermediate processing between edge devices and cloud.

---

Q86. Software Testing Definition?

Ans: Process to evaluate software for defects and ensure quality.

---

Q87. Types of Software Testing?

Ans:

• Manual Testing

• Automated Testing

• Functional Testing

• Non-Functional Testing

---

Q88. Black Box Testing?

Ans: Testing without knowing internal code; focuses on inputs and outputs.

---

Q89. White Box Testing?

Ans: Testing with knowledge of internal code; focuses on logic, paths, branches.

---

Q90. Unit Testing?

Ans: Testing individual modules/functions for correctness.

---

Q91. Integration Testing?

Ans: Testing combined modules to check interaction correctness.

---

Q92. System Testing?

Ans: Testing complete system against requirements.

---

Q93. Regression Testing?

Ans: Re-testing software after changes to ensure existing functionality is intact.

---

Q94. Performance Testing?

Ans: Evaluates system speed, scalability, and responsiveness.

---

Q95. Load Testing?

Ans: Checks system behavior under expected load.

---

Q96. Stress Testing?

Ans: Checks system behavior under extreme load conditions.

---

Q97. Software Metrics?

Ans: Quantitative measures to assess software quality, complexity, and performance.

---

Q98. SDLC Waterfall Model?

Ans: Linear sequential model with fixed phases; simple but inflexible.

---

Q99. SDLC Spiral Model?

Ans: Iterative model emphasizing risk analysis at each phase.

---

Q100. Agile vs Waterfall?

Ans:

• Agile → Iterative, flexible, collaborative

• Waterfall → Linear, rigid, phase-wise

🎓 MCA Semester-3 – Q101 to Q150

---

Q101. What is Indexing in DBMS?

Ans: Data structure that improves the speed of data retrieval operations on a database table.

---

Q102. Types of Indexing?

Ans:

• Single-Level Index

• Multi-Level Index

• Clustered Index

• Non-Clustered Index

---

Q103. B-Tree Indexing?

Ans: Balanced tree structure used to maintain sorted data and allow searches, sequential access, insertions, and deletions in logarithmic time.

---

Q104. B+ Tree Indexing?

Ans: Leaf nodes contain all data pointers; internal nodes contain keys only; supports range queries efficiently.

---

Q105. Hash Indexing?

Ans: Indexing using hash function; suitable for equality searches.

---

Q106. Concurrency in DBMS?

Ans: Ability of multiple transactions to execute simultaneously without violating database consistency.

---

Q107. Isolation Levels in DBMS?

Ans:

• Read Uncommitted

• Read Committed

• Repeatable Read

• Serializable

---

Q108. Dirty Read?

Ans: Transaction reads data written by another uncommitted transaction.

---

Q109. Lost Update Problem?

Ans: Two transactions overwrite each other’s updates leading to data inconsistency.

---

Q110. Phantom Problem?

Ans: Transaction reads a set of rows satisfying a condition; another transaction inserts/deletes rows affecting result in same query execution.

---

Q111. Two-Phase Locking (2PL)?

Ans: Concurrency control method; transactions acquire locks in growing phase and release in shrinking phase to ensure serializability.

---

Q112. Deadlock Handling Techniques?

Ans:

• Prevention

• Avoidance (Banker’s Algorithm)

• Detection & Recovery

---

Q113. ACID vs BASE?

Ans:

• ACID → Relational DB, strong consistency

• BASE → NoSQL, eventually consistent

---

Q114. Data Warehouse vs Data Mart?

Ans:

• Data Warehouse → Enterprise-level, integrated, large

• Data Mart → Department-level, focused, smaller

---

Q115. ETL Process?

Ans: Extract → Transform → Load; moves data from sources to warehouse.

---

Q116. OLAP Cube?

Ans: Multidimensional array of data for fast analytical queries.

---

Q117. ROLAP vs MOLAP?

Ans:

• ROLAP → Relational DB storage; scalable

• MOLAP → Multidimensional DB; faster queries

---

Q118. Hadoop vs Traditional DB?

Ans:

• Hadoop → Distributed, unstructured/semi-structured, scalable

• DB → Centralized, structured, ACID compliant

---

Q119. MapReduce Job Components?

Ans:

• Input Split → splits input files

• Mapper → processes input

• Shuffle & Sort → groups data

• Reducer → aggregates results

---

Q120. YARN Architecture?

Ans:

• ResourceManager → manages cluster resources

• NodeManager → manages single node

• ApplicationMaster → coordinates application execution

---

Q121. Spark RDD?

Ans: Resilient Distributed Dataset; immutable collection of objects distributed across cluster.

---

Q122. Spark Transformations vs Actions?

Ans:

• Transformation → creates new RDD (lazy evaluation)

• Action → triggers computation and returns result

---

Q123. HDFS vs Local File System?

Ans:

• HDFS → Distributed, fault-tolerant, large datasets

• Local FS → Single machine, limited size

---

Q124. Software Process Models?

Ans: Waterfall, Spiral, V-Model, Agile, RAD

---

Q125. Agile Principles?

Ans:

• Customer collaboration

• Working software

• Responding to change

• Individuals & interactions

---

Q126. Scrum Artifacts?

Ans: Product Backlog, Sprint Backlog, Increment

---

Q127. Scrum Ceremonies?

Ans: Sprint Planning, Daily Standup, Sprint Review, Sprint Retrospective

---

Q128. Cloud Deployment Models?

Ans: Public, Private, Hybrid, Community

---

Q129. Cloud Service Models?

Ans: IaaS, PaaS, SaaS

---

Q130. Advantages of Virtualization?

Ans:

• Resource optimization

• Isolation

• Scalability

• Backup & recovery

---

Q131. Big Data Characteristics?

Ans: 5Vs – Volume, Velocity, Variety, Veracity, Value

---

Q132. Hadoop Components?

Ans: HDFS, MapReduce, YARN, Hive, Pig, HBase, Sqoop, Flume

---

Q133. HDFS Replication?

Ans: Default 3 copies for fault tolerance; blocks distributed across cluster nodes.

---

Q134. HDFS Block Size?

Ans: Default 128 MB per block; configurable.

---

Q135. Spark vs Hadoop MapReduce?

Ans:

• Spark → In-memory, faster, supports batch & real-time

• Hadoop → Disk-based, batch processing

---

Q136. Data Mining vs Data Warehousing?

Ans:

• Data Mining → Extract patterns from data

• Data Warehousing → Storage of integrated historical data

---

Q137. ETL vs ELT?

Ans:

• ETL → Transform before Load

• ELT → Load before Transform (used in Big Data)

---

Q138. Normalization Levels?

Ans: 1NF, 2NF, 3NF, BCNF, 4NF, 5NF

---

Q139. Functional Dependency?

Ans: Attribute B is functionally dependent on A if value of A determines B.

---

Q140. Join Types in SQL?

Ans: Inner Join, Left Join, Right Join, Full Outer Join, Cross Join

---

Q141. ACID Properties in DBMS?

Ans: Atomicity, Consistency, Isolation, Durability

---

Q142. CAP Theorem?

Ans: A distributed system can provide at most 2 of 3: Consistency, Availability, Partition Tolerance.

---

Q143. NoSQL Database Types?

Ans: Key-Value, Document, Column-Family, Graph

---

Q144. OLTP vs OLAP?

Ans: OLTP → transactional; OLAP → analytical

---

Q145. Data Cube Operations?

Ans: Roll-up, Drill-down, Slice, Dice, Pivot

---

Q146. Hadoop Advantages?

Ans: Scalability, Fault Tolerance, Cost Efficiency, Flexibility

---

Q147. Spark Advantages?

Ans: In-memory computing, Real-time processing, Easy API

---

Q148. Data Mining Techniques?

Ans: Classification, Clustering, Association Rule Mining, Regression

---

Q149. Clustering Algorithms?

Ans: K-Means, Hierarchical, DBSCAN

---

Q150. Classification Algorithms?

Ans: Decision Tree, Naive Bayes, Random Forest, SVM

🎓 MCA Semester-3 – Q151 to Q200

---

Q151. What is a Transaction in DBMS?

Ans: A sequence of one or more operations on a database treated as a single logical unit.

---

Q152. Types of Database Transactions?

Ans:

• Read-only Transaction

• Update Transaction

---

Q153. Properties of a Transaction?

Ans: ACID – Atomicity, Consistency, Isolation, Durability

---

Q154. Concurrency Control Techniques?

Ans:

• Lock-based Protocols

• Time-stamp Ordering

• Optimistic Concurrency Control

---

Q155. Deadlock in DBMS?

Ans: A situation where two or more transactions wait indefinitely for resources held by each other.

---

Q156. Deadlock Prevention in DBMS?

Ans: Prevent one of the necessary conditions for deadlock (Mutual Exclusion, Hold & Wait, No Preemption, Circular Wait).

---

Q157. Deadlock Detection?

Ans: Maintain Wait-For graph and detect cycles to identify deadlocks.

---

Q158. Two-Phase Locking (2PL)?

Ans: Transactions acquire locks in growing phase and release locks in shrinking phase to ensure serializability.

---

Q159. Isolation Levels?

Ans: Read Uncommitted, Read Committed, Repeatable Read, Serializable

---

Q160. Dirty Read, Non-Repeatable Read, Phantom Read?

Ans:

• Dirty Read → Reading uncommitted data

• Non-Repeatable Read → Data changes between reads

• Phantom Read → New row appears in repeated query

---

Q161. Big Data Definition?

Ans: Extremely large and complex datasets that cannot be handled by traditional data processing techniques.

---

Q162. Characteristics of Big Data?

Ans: 5Vs – Volume, Velocity, Variety, Veracity, Value

---

Q163. Hadoop Components?

Ans: HDFS, MapReduce, YARN, Hive, Pig, HBase, Sqoop, Flume

---

Q164. HDFS Features?

Ans: Distributed storage, Fault-tolerant, Large file support, High throughput

---

Q165. MapReduce Concept?

Ans: Programming model for parallel processing of large datasets using Mapper and Reducer functions.

---

Q166. Spark RDD?

Ans: Resilient Distributed Dataset; immutable, partitioned collection of data distributed across cluster nodes.

---

Q167. Transformations vs Actions in Spark?

Ans:

• Transformations → Lazy operations creating new RDD

• Actions → Execute computations and return results

---

Q168. YARN in Hadoop?

Ans: Resource manager handling job scheduling and cluster resource allocation.

---

Q169. NoSQL Databases?

Ans: Non-relational databases handling unstructured or semi-structured data with scalability (e.g., MongoDB, Cassandra).

---

Q170. Types of NoSQL Databases?

Ans: Key-Value, Document, Column-Family, Graph

---

Q171. CAP Theorem?

Ans: In a distributed system, only 2 of the 3 can be guaranteed: Consistency, Availability, Partition Tolerance.

---

Q172. Cloud Computing?

Ans: Delivery of computing services (servers, storage, DB, software) over the Internet.

---

Q173. Cloud Service Models?

Ans: IaaS, PaaS, SaaS

---

Q174. Cloud Deployment Models?

Ans: Public, Private, Hybrid, Community

---

Q175. Advantages of Cloud Computing?

Ans: Scalability, Cost Efficiency, Accessibility, High Availability

---

Q176. Disadvantages of Cloud Computing?

Ans: Security Risks, Internet dependency, Downtime, Limited control

---

Q177. Edge Computing?

Ans: Processing data near the source to reduce latency.

---

Q178. Fog Computing?

Ans: Intermediate layer between cloud and edge devices for distributed processing.

---

Q179. Software Engineering Definition?

Ans: Systematic approach to design, develop, test, and maintain software.

---

Q180. SDLC Phases?

Ans: Requirement Analysis, Design, Implementation, Testing, Deployment, Maintenance

---

Q181. Waterfall Model?

Ans: Linear sequential SDLC model; simple but inflexible to changes.

---

Q182. Spiral Model?

Ans: Iterative model focusing on risk analysis at each phase; combines prototyping and waterfall.

---

Q183. Agile Methodology?

Ans: Iterative, collaborative approach prioritizing working software and customer feedback.

---

Q184. Scrum Roles?

Ans: Product Owner, Scrum Master, Development Team

---

Q185. Scrum Artifacts?

Ans: Product Backlog, Sprint Backlog, Increment

---

Q186. Scrum Ceremonies?

Ans: Sprint Planning, Daily Standup, Sprint Review, Sprint Retrospective

---

Q187. Software Testing?

Ans: Process to evaluate software for defects and ensure quality.

---

Q188. Types of Testing?

Ans: Manual, Automated, Functional, Non-Functional

---

Q189. Black Box Testing?

Ans: Testing without knowledge of internal code; focuses on input/output.

---

Q190. White Box Testing?

Ans: Testing with knowledge of code; focuses on logic, paths, and branches.

---

Q191. Unit Testing?

Ans: Testing individual modules/functions for correctness.

---

Q192. Integration Testing?

Ans: Testing combined modules for correct interactions.

---

Q193. System Testing?

Ans: Testing complete system against requirements.

---

Q194. Regression Testing?

Ans: Re-testing software after modifications to ensure existing functionalities work.

---

Q195. Performance Testing?

Ans: Evaluates system responsiveness, scalability, and stability.

---

Q196. Load Testing?

Ans: Tests system behavior under expected workload.

---

Q197. Stress Testing?

Ans: Tests system behavior under extreme workload.

---

Q198. Functional vs Non-Functional Testing?

Ans:

• Functional → Verifies features and functionalities

• Non-Functional → Verifies performance, usability, reliability

---

Q199. Software Metrics?

Ans: Quantitative measures to assess software quality, complexity, and performance.

---

Q200. Differences between OLTP and OLAP?

Ans:

• OLTP → Transactional, frequent inserts/updates, normalized data

• OLAP → Analytical, complex queries, denormalized data

🎓 MCA Semester-3 – Q201 to Q250

---

Q201. Difference between SQL and NoSQL?

Ans:

• SQL → Relational, structured, ACID, vertical scaling

• NoSQL → Non-relational, unstructured/semi-structured, eventual consistency, horizontal scaling

---

Q202. Examples of SQL Databases?

Ans: MySQL, PostgreSQL, Oracle, MS SQL Server

---

Q203. Examples of NoSQL Databases?

Ans: MongoDB, Cassandra, Redis, Neo4j

---

Q204. Hadoop Advantages?

Ans: Distributed storage, fault-tolerance, scalability, cost-efficient, supports large datasets

---

Q205. Hadoop Limitations?

Ans: High latency for small jobs, complex programming, not suitable for real-time processing

---

Q206. Components of Hadoop Ecosystem?

Ans: HDFS, MapReduce, YARN, Hive, Pig, HBase, Sqoop, Flume, Oozie

---

Q207. Features of HDFS?

Ans: Distributed, fault-tolerant, high throughput, large file support, block-based storage

---

Q208. HDFS Block Replication?

Ans: Default 3 replicas; blocks stored across different nodes for fault tolerance

---

Q209. What is YARN?

Ans: Yet Another Resource Negotiator; Hadoop resource manager for job scheduling and cluster resource management

---

Q210. MapReduce Job Flow?

Ans: Input Split → Map → Shuffle & Sort → Reduce → Output

---

Q211. Spark Features?

Ans: In-memory processing, Resilient Distributed Datasets (RDDs), supports batch and real-time processing

---

Q212. Transformations in Spark?

Ans: map(), filter(), flatMap(), groupByKey(), reduceByKey()

---

Q213. Actions in Spark?

Ans: count(), collect(), reduce(), saveAsTextFile(), take()

---

Q214. RDD vs DataFrame vs Dataset?

Ans:

• RDD → Low-level, untyped

• DataFrame → Schema, optimized

• Dataset → Typed, combines RDD and DataFrame features

---

Q215. Edge Computing vs Cloud Computing?

Ans:

• Edge → Processing near data source, low latency

• Cloud → Centralized processing, scalable, higher latency

---

Q216. Cloud Security Measures?

Ans: Encryption, Access Control, Firewalls, Intrusion Detection, Backup & Recovery

---

Q217. Multi-Tenancy in Cloud?

Ans: Single instance serves multiple users with logical data separation

---

Q218. Types of Cloud Services?

Ans: IaaS, PaaS, SaaS

---

Q219. Cloud Deployment Models?

Ans: Public, Private, Hybrid, Community

---

Q220. Advantages of Agile Methodology?

Ans: Faster delivery, customer feedback, adaptability to change, improved collaboration

---

Q221. Scrum Roles?

Ans: Product Owner, Scrum Master, Development Team

---

Q222. Scrum Artifacts?

Ans: Product Backlog, Sprint Backlog, Increment

---

Q223. Scrum Ceremonies?

Ans: Sprint Planning, Daily Standup, Sprint Review, Sprint Retrospective

---

Q224. Software Testing Types?

Ans: Unit, Integration, System, Regression, Performance, Load, Stress

---

Q225. Black Box Testing?

Ans: Testing without internal code knowledge; focuses on inputs and outputs

---

Q226. White Box Testing?

Ans: Testing with code knowledge; focuses on logic, paths, branches

---

Q227. Unit Testing?

Ans: Testing individual functions or modules for correctness

---

Q228. Integration Testing?

Ans: Testing combined modules to ensure they work together correctly

---

Q229. System Testing?

Ans: Testing entire system against requirements

---

Q230. Regression Testing?

Ans: Re-testing software after changes to ensure existing functionality is intact

---

Q231. Performance Testing?

Ans: Evaluates system speed, scalability, stability, and responsiveness

---

Q232. Load Testing?

Ans: Checks system behavior under expected workload

---

Q233. Stress Testing?

Ans: Checks system behavior under extreme or peak loads

---

Q234. Functional vs Non-Functional Testing?

Ans:

• Functional → Verifies features

• Non-Functional → Verifies performance, usability, reliability

---

Q235. Software Metrics?

Ans: Quantitative measures to assess software quality, complexity, performance, and maintainability

---

Q236. Difference between OLTP and OLAP?

Ans:

• OLTP → Transactional systems, frequent inserts/updates, normalized

• OLAP → Analytical systems, complex queries, denormalized

---

Q237. Data Cube Operations?

Ans: Roll-up, Drill-down, Slice, Dice, Pivot

---

Q238. Star Schema vs Snowflake Schema?

Ans:

• Star → Central fact table, denormalized dimensions

• Snowflake → Normalized dimensions, more complex

---

Q239. Data Mining vs Data Warehousing?

Ans:

• Data Mining → Extract patterns from data

• Data Warehousing → Store historical and integrated data

---

Q240. ETL vs ELT?

Ans:

• ETL → Transform before Load

• ELT → Load before Transform

---

Q241. Normalization Levels?

Ans: 1NF, 2NF, 3NF, BCNF, 4NF, 5NF

---

Q242. Functional Dependency?

Ans: Attribute B is functionally dependent on A if value of A determines B

---

Q243. Join Types in SQL?

Ans: Inner, Left, Right, Full Outer, Cross Join

---

Q244. ACID Properties in DBMS?

Ans: Atomicity, Consistency, Isolation, Durability

---

Q245. CAP Theorem?

Ans: Only 2 of 3 properties can be guaranteed: Consistency, Availability, Partition Tolerance

---

Q246. NoSQL Database Types?

Ans: Key-Value, Document, Column-Family, Graph

---

Q247. Hadoop vs Spark?

Ans:

• Hadoop → Disk-based, batch processing

• Spark → In-memory, batch & real-time processing, faster

---

Q248. HDFS NameNode vs DataNode?

Ans:

• NameNode → Manages metadata and namespace

• DataNode → Stores actual data blocks

---

Q249. Hive vs Pig?

Ans:

• Hive → SQL-like query language for analysts

• Pig → Script-based processing for programmers

---

Q250. HBase Features?

Ans: Column-oriented, NoSQL, real-time read/write, scalable

🎓 MCA Semester-3 – Q251 to Q300

---

Q251. What is Data Mining?

Ans: Process of discovering patterns, correlations, and knowledge from large datasets.

---

Q252. Data Mining Techniques?

Ans: Classification, Clustering, Association Rule Mining, Regression

---

Q253. Classification in Data Mining?

Ans: Assigning items to predefined categories based on attributes (e.g., Decision Tree, SVM)

---

Q254. Clustering in Data Mining?

Ans: Grouping similar items together without predefined labels (e.g., K-Means)

---

Q255. Association Rule Mining?

Ans: Discovering relationships among variables in large datasets (e.g., Market Basket Analysis)

---

Q256. Apriori Algorithm?

Ans: Algorithm to find frequent itemsets and association rules in transactional data.

---

Q257. Decision Tree?

Ans: Tree structure used for classification and prediction based on attribute values.

---

Q258. Random Forest?

Ans: Ensemble of multiple decision trees; improves accuracy and reduces overfitting.

---

Q259. SVM (Support Vector Machine)?

Ans: Supervised machine learning algorithm; finds optimal hyperplane separating classes.

---

Q260. Hadoop vs Traditional DBMS?

Ans:

• Hadoop → Distributed, scalable, supports unstructured/semi-structured data

• DBMS → Centralized, structured data, ACID compliant

---

Q261. HDFS Features?

Ans: Distributed storage, fault-tolerant, high throughput, block-based storage

---

Q262. HDFS Block Size?

Ans: Default 128MB per block; configurable

---

Q263. HDFS Replication?

Ans: Default 3 replicas for fault tolerance; blocks distributed across cluster nodes

---

Q264. NameNode vs DataNode?

Ans:

• NameNode → Metadata and namespace management

• DataNode → Stores actual data blocks

---

Q265. MapReduce Concept?

Ans: Programming model for parallel processing of large datasets using Mapper and Reducer

---

Q266. Spark Features?

Ans: In-memory processing, RDDs, batch and real-time processing, fault-tolerant

---

Q267. RDD in Spark?

Ans: Resilient Distributed Dataset; immutable collection of data distributed across cluster

---

Q268. Transformations in Spark?

Ans: map(), filter(), flatMap(), groupByKey(), reduceByKey()

---

Q269. Actions in Spark?

Ans: count(), collect(), reduce(), saveAsTextFile(), take()

---

Q270. Spark DataFrame vs RDD?

Ans:

• RDD → Low-level, untyped, more control

• DataFrame → Optimized, schema-aware, higher-level API

---

Q271. YARN Architecture?

Ans:

• ResourceManager → Manages cluster resources

• NodeManager → Manages node-level resources

• ApplicationMaster → Coordinates job execution

---

Q272. OLTP vs OLAP?

Ans:

• OLTP → Transactional systems, frequent inserts/updates

• OLAP → Analytical systems, complex queries, read-heavy

---

Q273. Data Cube Operations?

Ans: Roll-up, Drill-down, Slice, Dice, Pivot

---

Q274. Star Schema vs Snowflake Schema?

Ans:

• Star → Central fact table, denormalized dimensions

• Snowflake → Normalized dimensions, more complex queries

---

Q275. ETL Process?

Ans: Extract → Transform → Load; moves data from source to data warehouse

---

Q276. ELT vs ETL?

Ans:

• ETL → Transform before load

• ELT → Load before transform

---

Q277. Functional Dependency?

Ans: Attribute B is functionally dependent on A if value of A determines value of B

---

Q278. Normalization Levels?

Ans: 1NF, 2NF, 3NF, BCNF, 4NF, 5NF

---

Q279. Join Types in SQL?

Ans: Inner Join, Left Join, Right Join, Full Outer Join, Cross Join

---

Q280. ACID Properties?

Ans: Atomicity, Consistency, Isolation, Durability

---

Q281. Concurrency Control in DBMS?

Ans: Techniques to ensure correct execution of simultaneous transactions

---

Q282. Two-Phase Locking (2PL)?

Ans: Transactions acquire locks in growing phase and release in shrinking phase to ensure serializability

---

Q283. Isolation Levels?

Ans: Read Uncommitted, Read Committed, Repeatable Read, Serializable

---

Q284. Dirty Read, Non-Repeatable Read, Phantom Read?

Ans:

• Dirty Read → Reading uncommitted data

• Non-Repeatable Read → Data changes between reads

• Phantom Read → New row appears in repeated query

---

Q285. Cloud Computing Definition?

Ans: Delivery of computing services over the Internet, including servers, storage, databases, and applications

---

Q286. Cloud Service Models?

Ans: IaaS, PaaS, SaaS

---

Q287. Cloud Deployment Models?

Ans: Public, Private, Hybrid, Community

---

Q288. Advantages of Cloud Computing?

Ans: Scalability, Cost-efficiency, Accessibility, High Availability

---

Q289. Disadvantages of Cloud Computing?

Ans: Security Risks, Internet dependency, Downtime, Limited control

---

Q290. Multi-Tenancy in Cloud?

Ans: Single instance of software serves multiple customers with data isolation

---

Q291. Edge Computing?

Ans: Processing data near the source to reduce latency

---

Q292. Fog Computing?

Ans: Intermediate layer between edge devices and cloud for distributed processing

---

Q293. Agile Methodology?

Ans: Iterative, flexible approach prioritizing customer collaboration and working software

---

Q294. Scrum Roles?

Ans: Product Owner, Scrum Master, Development Team

---

Q295. Scrum Artifacts?

Ans: Product Backlog, Sprint Backlog, Increment

---

Q296. Scrum Ceremonies?

Ans: Sprint Planning, Daily Standup, Sprint Review, Sprint Retrospective

---

Q297. Software Testing Types?

Ans: Unit, Integration, System, Regression, Performance, Load, Stress

---

Q298. Black Box Testing?

Ans: Testing without internal code knowledge; focuses on input/output

---

Q299. White Box Testing?

Ans: Testing with knowledge of internal code; focuses on logic, paths, branches

---

Q300. Unit Testing?

Ans: Testing individual functions or modules to ensure correctness

🎓 MCA Semester-3 – Q301 to Q350

---

Q301. Integration Testing?

Ans: Testing combined modules to ensure they work together correctly.

---

Q302. System Testing?

Ans: Testing the entire system against requirements to ensure functionality.

---

Q303. Regression Testing?

Ans: Re-testing software after changes to verify existing functionality remains intact.

---

Q304. Performance Testing?

Ans: Evaluates system responsiveness, throughput, and stability under load.

---

Q305. Load Testing?

Ans: Checks system behavior under expected user load.

---

Q306. Stress Testing?

Ans: Evaluates system performance under extreme load conditions.

---

Q307. Functional Testing?

Ans: Verifies software features and functionalities against requirements.

---

Q308. Non-Functional Testing?

Ans: Evaluates performance, usability, reliability, and security of software.

---

Q309. Software Metrics?

Ans: Quantitative measures to assess software quality, complexity, and maintainability.

---

Q310. Waterfall Model?

Ans: Linear SDLC model with sequential phases; simple but inflexible.

---

Q311. Spiral Model?

Ans: Iterative model emphasizing risk analysis at each phase; combines prototyping and waterfall.

---

Q312. Agile Model?

Ans: Iterative and incremental model emphasizing flexibility, collaboration, and customer feedback.

---

Q313. Scrum Methodology?

Ans: Agile framework with roles, artifacts, and ceremonies for iterative development.

---

Q314. Scrum Roles?

Ans: Product Owner, Scrum Master, Development Team

---

Q315. Scrum Artifacts?

Ans: Product Backlog, Sprint Backlog, Increment

---

Q316. Scrum Ceremonies?

Ans: Sprint Planning, Daily Standup, Sprint Review, Sprint Retrospective

---

Q317. Cloud Computing Definition?

Ans: Delivery of computing services over the internet including servers, storage, databases, and software.

---

Q318. Cloud Service Models?

Ans: IaaS, PaaS, SaaS

---

Q319. Cloud Deployment Models?

Ans: Public, Private, Hybrid, Community

---

Q320. Advantages of Cloud Computing?

Ans: Scalability, Cost Efficiency, Accessibility, High Availability

---

Q321. Disadvantages of Cloud Computing?

Ans: Security Risks, Internet dependency, Downtime, Limited control

---

Q322. Virtualization?

Ans: Creating virtual instances of hardware resources for efficient utilization.

---

Q323. Edge Computing?

Ans: Processing data near the source to reduce latency.

---

Q324. Fog Computing?

Ans: Intermediate layer between cloud and edge devices for distributed processing.

---

Q325. Big Data Definition?

Ans: Extremely large datasets that cannot be processed using traditional methods.

---

Q326. Characteristics of Big Data?

Ans: 5Vs – Volume, Velocity, Variety, Veracity, Value

---

Q327. Hadoop Features?

Ans: Distributed storage, fault-tolerant, scalable, supports large datasets.

---

Q328. HDFS Block Size?

Ans: Default 128MB per block; configurable.

---

Q329. HDFS Replication Factor?

Ans: Default 3 replicas for fault tolerance.

---

Q330. NameNode vs DataNode?

Ans:

• NameNode → Manages metadata

• DataNode → Stores actual data blocks

---

Q331. MapReduce Concept?

Ans: Programming model for distributed data processing using Mapper and Reducer.

---

Q332. Spark Features?

Ans: In-memory computing, RDDs, batch & real-time processing, fault-tolerant.

---

Q333. RDD in Spark?

Ans: Resilient Distributed Dataset; immutable, distributed collection of data.

---

Q334. Transformations in Spark?

Ans: map(), filter(), flatMap(), groupByKey(), reduceByKey()

---

Q335. Actions in Spark?

Ans: count(), collect(), reduce(), saveAsTextFile(), take()

---

Q336. DataFrame vs RDD?

Ans:

• RDD → Low-level, untyped

• DataFrame → Schema-aware, optimized, high-level API

---

Q337. YARN Architecture?

Ans: ResourceManager, NodeManager, ApplicationMaster

---

Q338. OLTP vs OLAP?

Ans:

• OLTP → Transactional, normalized, frequent updates

• OLAP → Analytical, denormalized, complex queries

---

Q339. Data Cube Operations?

Ans: Roll-up, Drill-down, Slice, Dice, Pivot

---

Q340. Star Schema vs Snowflake Schema?

Ans:

• Star → Central fact table, denormalized dimensions

• Snowflake → Normalized dimensions, more complex queries

---

Q341. ETL Process?

Ans: Extract → Transform → Load data from source to warehouse

---

Q342. ELT vs ETL?

Ans:

• ETL → Transform before Load

• ELT → Load before Transform

---

Q343. Normalization Levels?

Ans: 1NF, 2NF, 3NF, BCNF, 4NF, 5NF

---

Q344. Functional Dependency?

Ans: Attribute B is functionally dependent on A if A determines B

---

Q345. SQL Join Types?

Ans: Inner, Left, Right, Full Outer, Cross Join

---

Q346. ACID Properties?

Ans: Atomicity, Consistency, Isolation, Durability

---

Q347. Concurrency Control?

Ans: Techniques to ensure correct execution of simultaneous transactions.

---

Q348. Two-Phase Locking (2PL)?

Ans: Growing phase to acquire locks, shrinking phase to release locks; ensures serializability.

---

Q349. Isolation Levels?

Ans: Read Uncommitted, Read Committed, Repeatable Read, Serializable

---

Q350. Dirty Read, Non-Repeatable Read, Phantom Read?

Ans:

• Dirty Read → Read uncommitted data

• Non-Repeatable Read → Data changes between reads

• Phantom Read → New row appears in repeated query

🎓 MCA Semester-3 – Q351 to Q400

---

Q351. What is Regression Testing?

Ans: Re-testing software after modifications to ensure existing functionality remains unaffected.

---

Q352. What is Unit Testing?

Ans: Testing individual functions or modules to ensure correctness.

---

Q353. What is Integration Testing?

Ans: Testing combined modules to verify correct interactions.

---

Q354. What is System Testing?

Ans: Testing the complete system against requirements.

---

Q355. Black Box Testing?

Ans: Testing without internal code knowledge; focuses on input/output behavior.

---

Q356. White Box Testing?

Ans: Testing with internal code knowledge; focuses on logic, paths, and branches.

---

Q357. Load Testing?

Ans: Tests system behavior under expected workload.

---

Q358. Stress Testing?

Ans: Tests system behavior under extreme conditions.

---

Q359. Functional Testing?

Ans: Verifies software features against requirements.

---

Q360. Non-Functional Testing?

Ans: Evaluates performance, usability, reliability, and security.

---

Q361. Performance Testing?

Ans: Measures system responsiveness, stability, and throughput.

---

Q362. Agile Methodology?

Ans: Iterative and incremental approach emphasizing customer collaboration and working software.

---

Q363. Scrum Framework?

Ans: Agile framework with defined roles, artifacts, and ceremonies.

---

Q364. Scrum Roles?

Ans: Product Owner, Scrum Master, Development Team

---

Q365. Scrum Artifacts?

Ans: Product Backlog, Sprint Backlog, Increment

---

Q366. Scrum Ceremonies?

Ans: Sprint Planning, Daily Standup, Sprint Review, Sprint Retrospective

---

Q367. Waterfall Model?

Ans: Linear sequential SDLC model; simple but rigid.

---

Q368. Spiral Model?

Ans: Iterative model emphasizing risk analysis at each phase.

---

Q369. Agile vs Waterfall?

Ans: Agile → Iterative, flexible, collaborative; Waterfall → Linear, rigid, phase-wise.

---

Q370. Cloud Computing?

Ans: Delivery of computing services over the Internet including servers, storage, databases, and applications.

---

Q371. Cloud Service Models?

Ans: IaaS, PaaS, SaaS

---

Q372. Cloud Deployment Models?

Ans: Public, Private, Hybrid, Community

---

Q373. Advantages of Cloud Computing?

Ans: Scalability, cost-efficiency, high availability, accessibility.

---

Q374. Disadvantages of Cloud Computing?

Ans: Security concerns, downtime risks, limited control, Internet dependency.

---

Q375. Multi-Tenancy in Cloud?

Ans: Single instance of software serves multiple users with logical data separation.

---

Q376. Virtualization in Cloud?

Ans: Creating virtual instances of hardware to optimize resource utilization.

---

Q377. Edge Computing?

Ans: Processing data near the source to reduce latency.

---

Q378. Fog Computing?

Ans: Intermediate processing layer between cloud and edge devices.

---

Q379. Big Data Definition?

Ans: Extremely large datasets that cannot be processed using traditional methods.

---

Q380. Big Data Characteristics?

Ans: Volume, Velocity, Variety, Veracity, Value (5Vs)

---

Q381. Hadoop Ecosystem Components?

Ans: HDFS, MapReduce, YARN, Hive, Pig, HBase, Sqoop, Flume, Oozie

---

Q382. HDFS Features?

Ans: Distributed storage, fault-tolerant, high throughput, block-based storage.

---

Q383. HDFS Block Size?

Ans: Default 128MB per block; configurable.

---

Q384. HDFS Replication Factor?

Ans: Default 3 replicas for fault tolerance.

---

Q385. NameNode vs DataNode?

Ans: NameNode manages metadata; DataNode stores actual data blocks.

---

Q386. MapReduce Job Flow?

Ans: Input Split → Map → Shuffle & Sort → Reduce → Output

---

Q387. Spark Features?

Ans: In-memory processing, RDDs, supports batch & real-time analytics.

---

Q388. RDD in Spark?

Ans: Resilient Distributed Dataset; immutable, distributed collection of data.

---

Q389. Spark Transformations?

Ans: map(), filter(), flatMap(), groupByKey(), reduceByKey()

---

Q390. Spark Actions?

Ans: count(), collect(), reduce(), saveAsTextFile(), take()

---

Q391. DataFrame vs RDD?

Ans: RDD → Low-level, untyped; DataFrame → Schema-aware, optimized, high-level API.

---

Q392. YARN Architecture?

Ans: ResourceManager, NodeManager, ApplicationMaster.

---

Q393. OLTP vs OLAP?

Ans: OLTP → Transactional; OLAP → Analytical.

---

Q394. Data Cube Operations?

Ans: Roll-up, Drill-down, Slice, Dice, Pivot.

---

Q395. Star Schema vs Snowflake Schema?

Ans: Star → Denormalized dimensions; Snowflake → Normalized dimensions.

---

Q396. ETL Process?

Ans: Extract → Transform → Load data from source to warehouse.

---

Q397. ELT vs ETL?

Ans: ETL → Transform before load; ELT → Load before transform.

---

Q398. Normalization Levels?

Ans: 1NF, 2NF, 3NF, BCNF, 4NF, 5NF.

---

Q399. Functional Dependency?

Ans: Attribute B is functionally dependent on A if A determines B.

---

Q400. ACID Properties?

Ans: Atomicity, Consistency, Isolation, Durability.

🎓 MCA Semester-3 – Q401 to Q450

---

Q401. Concurrency Control in DBMS?

Ans: Techniques to ensure correct execution of simultaneous transactions, e.g., locking, timestamp ordering.

---

Q402. Two-Phase Locking (2PL)?

Ans: Transactions acquire locks in growing phase and release in shrinking phase; ensures serializability.

---

Q403. Isolation Levels?

Ans: Read Uncommitted, Read Committed, Repeatable Read, Serializable.

---

Q404. Dirty Read?

Ans: Reading uncommitted data from another transaction.

---

Q405. Non-Repeatable Read?

Ans: Data changes between two reads within a transaction.

---

Q406. Phantom Read?

Ans: New rows appear in repeated query results within a transaction.

---

Q407. ACID Properties?

Ans: Atomicity, Consistency, Isolation, Durability.

---

Q408. CAP Theorem?

Ans: A distributed system can guarantee at most two of Consistency, Availability, Partition Tolerance.

---

Q409. NoSQL Databases?

Ans: Non-relational, scalable, supports unstructured/semi-structured data (e.g., MongoDB, Cassandra).

---

Q410. Types of NoSQL Databases?

Ans: Key-Value, Document, Column-Family, Graph.

---

Q411. OLTP vs OLAP?

Ans: OLTP → Transactional; OLAP → Analytical.

---

Q412. Data Cube Operations?

Ans: Roll-up, Drill-down, Slice, Dice, Pivot.

---

Q413. Star Schema vs Snowflake Schema?

Ans: Star → Denormalized; Snowflake → Normalized dimensions.

---

Q414. ETL vs ELT?

Ans: ETL → Transform before load; ELT → Load before transform.

---

Q415. Data Warehouse?

Ans: Central repository of integrated, historical, and structured data for analysis.

---

Q416. Data Mining?

Ans: Process of discovering patterns, correlations, and knowledge from data.

---

Q417. Classification in Data Mining?

Ans: Assigning items to predefined categories based on attributes.

---

Q418. Clustering in Data Mining?

Ans: Grouping similar items without predefined labels.

---

Q419. Association Rule Mining?

Ans: Discovering relationships among variables in datasets.

---

Q420. Apriori Algorithm?

Ans: Finds frequent itemsets and generates association rules.

---

Q421. Decision Tree?

Ans: Tree structure used for classification and prediction.

---

Q422. Random Forest?

Ans: Ensemble of decision trees to improve accuracy and reduce overfitting.

---

Q423. SVM (Support Vector Machine)?

Ans: Supervised algorithm finding optimal hyperplane separating classes.

---

Q424. Hadoop Features?

Ans: Distributed storage, fault-tolerant, scalable, supports large datasets.

---

Q425. HDFS?

Ans: Hadoop Distributed File System; block-based storage with replication.

---

Q426. HDFS Block Size?

Ans: Default 128MB per block; configurable.

---

Q427. HDFS Replication Factor?

Ans: Default 3 for fault tolerance.

---

Q428. NameNode vs DataNode?

Ans: NameNode → metadata; DataNode → stores data blocks.

---

Q429. MapReduce Job Flow?

Ans: Input Split → Map → Shuffle & Sort → Reduce → Output.

---

Q430. Spark Features?

Ans: In-memory computing, RDDs, batch & real-time processing.

---

Q431. RDD in Spark?

Ans: Resilient Distributed Dataset; immutable, distributed data collection.

---

Q432. Transformations in Spark?

Ans: map(), filter(), flatMap(), groupByKey(), reduceByKey().

---

Q433. Actions in Spark?

Ans: count(), collect(), reduce(), saveAsTextFile(), take().

---

Q434. DataFrame vs RDD?

Ans: DataFrame → schema-aware, optimized; RDD → low-level, untyped.

---

Q435. YARN Architecture?

Ans: ResourceManager, NodeManager, ApplicationMaster.

---

Q436. Cloud Computing Definition?

Ans: Delivery of computing services over the internet.

---

Q437. Cloud Service Models?

Ans: IaaS, PaaS, SaaS.

---

Q438. Cloud Deployment Models?

Ans: Public, Private, Hybrid, Community.

---

Q439. Advantages of Cloud Computing?

Ans: Scalability, cost-efficiency, high availability, accessibility.

---

Q440. Disadvantages of Cloud Computing?

Ans: Security risks, downtime, limited control, internet dependency.

---

Q441. Multi-Tenancy?

Ans: Single software instance serving multiple users with logical separation.

---

Q442. Virtualization?

Ans: Creating virtual instances of hardware for resource optimization.

---

Q443. Edge Computing?

Ans: Processing near the data source to reduce latency.

---

Q444. Fog Computing?

Ans: Intermediate processing layer between cloud and edge.

---

Q445. Agile Methodology?

Ans: Iterative approach emphasizing collaboration and working software.

---

Q446. Scrum Framework?

Ans: Agile framework with defined roles, artifacts, and ceremonies.

---

Q447. Scrum Roles?

Ans: Product Owner, Scrum Master, Development Team.

---

Q448. Scrum Artifacts?

Ans: Product Backlog, Sprint Backlog, Increment.

---

Q449. Scrum Ceremonies?

Ans: Sprint Planning, Daily Standup, Sprint Review, Sprint Retrospective.

---

Q450. Software Testing Types?

Ans: Unit, Integration, System, Regression, Performance, Load, Stress.

🎓 MCA Semester-3 – Q451 to Q500

---

Q451. Unit Testing?

Ans: Testing individual modules or functions for correctness.

---

Q452. Integration Testing?

Ans: Testing combined modules to ensure they interact correctly.

---

Q453. System Testing?

Ans: Testing the entire system against functional and non-functional requirements.

---

Q454. Regression Testing?

Ans: Re-testing after changes to ensure existing functionality is intact.

---

Q455. Load Testing?

Ans: Testing system behavior under expected workload.

---

Q456. Stress Testing?

Ans: Evaluating system performance under extreme conditions.

---

Q457. Performance Testing?

Ans: Measures responsiveness, stability, and throughput.

---

Q458. Functional Testing?

Ans: Verifies software features against specified requirements.

---

Q459. Non-Functional Testing?

Ans: Evaluates performance, reliability, usability, and security.

---

Q460. Black Box Testing?

Ans: Testing without knowledge of internal code; focuses on input/output.

---

Q461. White Box Testing?

Ans: Testing with knowledge of internal code; focuses on logic and paths.

---

Q462. Agile Methodology?

Ans: Iterative approach emphasizing collaboration and customer feedback.

---

Q463. Scrum Framework?

Ans: Agile framework with defined roles, artifacts, and ceremonies.

---

Q464. Scrum Roles?

Ans: Product Owner, Scrum Master, Development Team.

---

Q465. Scrum Artifacts?

Ans: Product Backlog, Sprint Backlog, Increment.

---

Q466. Scrum Ceremonies?

Ans: Sprint Planning, Daily Standup, Sprint Review, Sprint Retrospective.

---

Q467. Waterfall Model?

Ans: Linear sequential SDLC model; simple but rigid.

---

Q468. Spiral Model?

Ans: Iterative SDLC model emphasizing risk assessment.

---

Q469. Agile vs Waterfall?

Ans: Agile → Iterative and flexible; Waterfall → Linear and rigid.

---

Q470. Cloud Computing?

Ans: Delivery of computing services over the Internet.

---

Q471. Cloud Service Models?

Ans: IaaS, PaaS, SaaS.

---

Q472. Cloud Deployment Models?

Ans: Public, Private, Hybrid, Community.

---

Q473. Advantages of Cloud Computing?

Ans: Scalability, cost-efficiency, high availability, accessibility.

---

Q474. Disadvantages of Cloud Computing?

Ans: Security risks, downtime, limited control, Internet dependency.

---

Q475. Multi-Tenancy?

Ans: Single software instance serves multiple users with logical separation.

---

Q476. Virtualization?

Ans: Creating virtual instances of hardware for optimized resource use.

---

Q477. Edge Computing?

Ans: Processing near data source to reduce latency.

---

Q478. Fog Computing?

Ans: Intermediate processing layer between edge devices and cloud.

---

Q479. Big Data Definition?

Ans: Extremely large datasets that require specialized processing.

---

Q480. Big Data Characteristics?

Ans: 5Vs – Volume, Velocity, Variety, Veracity, Value.

---

Q481. Hadoop Ecosystem Components?

Ans: HDFS, MapReduce, YARN, Hive, Pig, HBase, Sqoop, Flume, Oozie.

---

Q482. HDFS Features?

Ans: Distributed, fault-tolerant, high throughput, block-based storage.

---

Q483. HDFS Block Size?

Ans: Default 128MB per block; configurable.

---

Q484. HDFS Replication Factor?

Ans: Default 3 replicas for fault tolerance.

---

Q485. NameNode vs DataNode?

Ans: NameNode → metadata; DataNode → stores actual blocks.

---

Q486. MapReduce Job Flow?

Ans: Input Split → Map → Shuffle & Sort → Reduce → Output.

---

Q487. Spark Features?

Ans: In-memory processing, RDDs, batch & real-time analytics.

---

Q488. RDD in Spark?

Ans: Resilient Distributed Dataset; immutable, partitioned collection of data.

---

Q489. Transformations in Spark?

Ans: map(), filter(), flatMap(), groupByKey(), reduceByKey().

---

Q490. Actions in Spark?

Ans: count(), collect(), reduce(), saveAsTextFile(), take().

---

Q491. DataFrame vs RDD?

Ans: DataFrame → schema-aware, optimized; RDD → low-level, untyped.

---

Q492. YARN Architecture?

Ans: ResourceManager, NodeManager, ApplicationMaster.

---

Q493. OLTP vs OLAP?

Ans: OLTP → Transactional; OLAP → Analytical.

---

Q494. Data Cube Operations?

Ans: Roll-up, Drill-down, Slice, Dice, Pivot.

---

Q495. Star Schema vs Snowflake Schema?

Ans: Star → denormalized dimensions; Snowflake → normalized dimensions.

---

Q496. ETL Process?

Ans: Extract → Transform → Load data from source to warehouse.

---

Q497. ELT vs ETL?

Ans: ETL → Transform before Load; ELT → Load before Transform.

---

Q498. Normalization Levels?

Ans: 1NF, 2NF, 3NF, BCNF, 4NF, 5NF.

---

Q499. Functional Dependency?

Ans: Attribute B is functionally dependent on A if A determines B.

---

Q500. ACID Properties?

Ans: Atomicity, Consistency, Isolation, Durability.

🎓 MCA Semester-4 – Q1 to Q50 (Start)

---

Q1. What is Java Reflection?

Ans: API that allows inspection and manipulation of classes, methods, and fields at runtime.

---

Q2. Differences between JDK, JRE, and JVM?

Ans:

• JVM → Executes Java bytecode.

• JRE → JVM + Libraries to run Java programs.

• JDK → JRE + Tools for Java development (compiler, debugger).

---

Q3. What is Java Multithreading?

Ans: Concurrent execution of two or more threads for parallel processing.

---

Q4. Thread Lifecycle in Java?

Ans: New → Runnable → Running → Waiting/Blocked → Terminated.

---

Q5. Synchronized Keyword in Java?

Ans: Used to control access to critical sections, ensuring thread safety.

---

Q6. Difference between Process and Thread?

Ans:

• Process → Independent, own memory; Thread → Lightweight, shares memory.

---

Q7. Java Collections Framework?

Ans: Set of classes/interfaces for storing and manipulating groups of objects (List, Set, Map, Queue).

---

Q8. Difference between ArrayList and LinkedList?

Ans:

• ArrayList → Dynamic array, fast access, slow insertion/deletion.

• LinkedList → Doubly linked list, slow access, fast insertion/deletion.

---

Q9. HashMap vs Hashtable?

Ans:

• HashMap → Non-synchronized, allows null keys/values.

• Hashtable → Synchronized, no null keys/values.

---

Q10. Difference between Comparable and Comparator?

Ans:

• Comparable → Single sorting logic in class (compareTo()).

• Comparator → Multiple sorting logic externally (compare()).

---

Q11. JDBC in Java?

Ans: Java Database Connectivity; API to connect Java applications with databases.

---

Q12. Steps in JDBC Programming?

Ans: Load Driver → Establish Connection → Create Statement → Execute Query → Process Result → Close Connection.

---

Q13. PreparedStatement vs Statement?

Ans:

• Statement → Executes static SQL; vulnerable to SQL injection.

• PreparedStatement → Precompiled SQL; secure & faster.

---

Q14. Transactions in JDBC?

Ans: Set of SQL operations executed as a single unit with commit and rollback support.

---

Q15. What is Servlets in Java?

Ans: Server-side Java programs handling requests and generating dynamic content.

---

Q16. Servlet Lifecycle?

Ans: Loading → Initialization → Service → Destroy.

---

Q17. Difference between doGet() and doPost()?

Ans:

• doGet → Appends data in URL, limited size, less secure.

• doPost → Sends data in body, more secure, no size limit.

---

Q18. What is JSP?

Ans: Java Server Pages; allows embedding Java code in HTML for dynamic web content.

---

Q19. JSP vs Servlets?

Ans:

• JSP → Easier for presentation (HTML-heavy).

• Servlet → Easier for business logic (Java-heavy).

---

Q20. MVC Architecture?

Ans: Model-View-Controller; separates data (Model), UI (View), and logic (Controller).

---

Q21. Advantages of MVC?

Ans: Separation of concerns, maintainability, reusability, parallel development.

---

Q22. Hibernate in Java?

Ans: ORM framework mapping Java objects to database tables.

---

Q23. Advantages of Hibernate?

Ans: Database independence, caching, lazy loading, automatic table mapping.

---

Q24. SessionFactory vs Session in Hibernate?

Ans:

• SessionFactory → Factory for Session objects; thread-safe.

• Session → Single unit of work with database; not thread-safe.

---

Q25. HQL in Hibernate?

Ans: Hibernate Query Language; database-independent object-oriented query language.

---

Q26. Difference between Lazy and Eager Loading?

Ans:

• Lazy → Loads data on demand.

• Eager → Loads data immediately.

---

Q27. Spring Framework?

Ans: Java framework for building enterprise applications with IoC and AOP support.

---

Q28. What is IoC in Spring?

Ans: Inversion of Control; framework manages object creation and dependency injection.

---

Q29. Dependency Injection Types?

Ans: Constructor Injection, Setter Injection, Field Injection.

---

Q30. Spring MVC?

Ans: Web framework based on MVC pattern; separates request handling, business logic, and view rendering.

---

Q31. RESTful Web Services?

Ans: Web services following REST principles (stateless, CRUD via HTTP methods).

---

Q32. HTTP Methods?

Ans: GET, POST, PUT, DELETE, PATCH, OPTIONS.

---

Q33. Difference between SOAP and REST?

Ans:

• SOAP → Protocol, XML-based, rigid.

• REST → Architectural style, JSON/XML, lightweight.

---

Q34. Big Data Characteristics?

Ans: 5Vs – Volume, Velocity, Variety, Veracity, Value.

---

Q35. Hadoop Ecosystem?

Ans: HDFS, MapReduce, YARN, Hive, Pig, HBase, Sqoop, Flume, Oozie.

---

Q36. HDFS Features?

Ans: Distributed, fault-tolerant, block storage, scalable.

---

Q37. HDFS Block Size?

Ans: Default 128MB; configurable.

---

Q38. MapReduce Concept?

Ans: Programming model for parallel processing; Map → Shuffle/Sort → Reduce.

---

Q39. Spark Features?

Ans: In-memory processing, RDDs, batch & real-time processing.

---

Q40. RDD vs DataFrame?

Ans: RDD → low-level, untyped; DataFrame → schema-aware, optimized.

---

Q41. Edge vs Cloud Computing?

Ans: Edge → Near data source, low latency; Cloud → Centralized, scalable.

---

Q42. Advantages of Cloud Computing?

Ans: Scalability, cost efficiency, accessibility, high availability.

---

Q43. Cloud Service Models?

Ans: IaaS, PaaS, SaaS.

---

Q44. Cloud Deployment Models?

Ans: Public, Private, Hybrid, Community.

---

Q45. Multi-Tenancy?

Ans: Single instance serving multiple users with logical separation.

---

Q46. Virtualization?

Ans: Creating virtual instances of hardware for optimized resource use.

---

Q47. Agile Methodology?

Ans: Iterative approach emphasizing collaboration and working software.

---

Q48. Scrum Roles?

Ans: Product Owner, Scrum Master, Development Team.

---

Q49. Scrum Artifacts?

Ans: Product Backlog, Sprint Backlog, Increment.

---

Q50. Scrum Ceremonies?

Ans: Sprint Planning, Daily Standup, Sprint Review, Sprint Retrospective.

🎓 MCA Semester-4 – Q51 to Q100

---

Q51. What is Spring Boot?

Ans: Framework simplifying Spring application development; provides auto-configuration and embedded servers.

---

Q52. Advantages of Spring Boot?

Ans: Rapid development, embedded servers, minimal configuration, production-ready features.

---

Q53. What is AOP in Spring?

Ans: Aspect-Oriented Programming; separates cross-cutting concerns like logging, security, transactions.

---

Q54. What is Bean in Spring?

Ans: Object managed by Spring IoC container.

---

Q55. Scope of Spring Bean?

Ans: Singleton, Prototype, Request, Session, Global Session.

---

Q56. What is REST Controller in Spring?

Ans: Controller annotated with @RestController; returns data as JSON/XML.

---

Q57. Difference between @Controller and @RestController?

Ans: @Controller → returns view; @RestController → returns data (JSON/XML).

---

Q58. Hibernate vs JDBC?

Ans: Hibernate → ORM, database-independent, automatic mapping.
JDBC → Manual SQL, database-specific.

---

Q59. Lazy vs Eager Loading in Hibernate?

Ans: Lazy → loads data on demand.
Eager → loads data immediately.

---

Q60. What is HQL?

Ans: Hibernate Query Language; object-oriented, database-independent query language.

---

Q61. What is Java RMI?

Ans: Remote Method Invocation; allows invoking methods on remote Java objects.

---

Q62. Difference between RMI and Sockets?

Ans: RMI → object-oriented remote calls.
Sockets → low-level communication using streams.

---

Q63. What is JMS?

Ans: Java Messaging Service; API for asynchronous message communication between applications.

---

Q64. Types of JMS Messaging?

Ans: Point-to-Point (Queue), Publish/Subscribe (Topic).

---

Q65. Advantages of JMS?

Ans: Reliable, asynchronous, loosely-coupled communication.

---

Q66. What is Microservices Architecture?

Ans: Architecture where applications are built as small, independent services communicating via APIs.

---

Q67. Advantages of Microservices?

Ans: Scalability, maintainability, independent deployment, fault isolation.

---

Q68. Difference between Monolithic and Microservices?

Ans: Monolithic → Single deployable; Microservices → multiple independent services.

---

Q69. What is API Gateway?

Ans: Entry point for client requests in microservices; handles routing, authentication, and rate-limiting.

---

Q70. REST vs SOAP Web Services?

Ans: REST → lightweight, stateless, JSON/XML.
SOAP → protocol, XML-based, rigid.

---

Q71. HTTP Status Codes?

Ans: 200 OK, 201 Created, 400 Bad Request, 401 Unauthorized, 404 Not Found, 500 Internal Server Error.

---

Q72. What is JWT?

Ans: JSON Web Token; used for secure stateless authentication.

---

Q73. JWT Structure?

Ans: Header, Payload, Signature.

---

Q74. What is OAuth2?

Ans: Authorization framework enabling third-party apps to access resources securely.

---

Q75. OAuth2 Roles?

Ans: Resource Owner, Client, Authorization Server, Resource Server.

---

Q76. What is Big Data Analytics?

Ans: Process of examining large datasets to uncover hidden patterns, correlations, and insights.

---

Q77. Hadoop vs Spark?

Ans: Hadoop → Disk-based batch processing.
Spark → In-memory, fast, batch & real-time.

---

Q78. What is YARN?

Ans: Yet Another Resource Negotiator; manages resources in Hadoop cluster.

---

Q79. Components of Hadoop Ecosystem?

Ans: HDFS, MapReduce, YARN, Hive, Pig, HBase, Sqoop, Flume, Oozie.

---

Q80. What is HDFS?

Ans: Hadoop Distributed File System; stores data in blocks with replication.

---

Q81. HDFS Replication Factor?

Ans: Default 3; ensures fault tolerance.

---

Q82. What is MapReduce?

Ans: Programming model for processing large datasets using Mapper and Reducer functions.

---

Q83. MapReduce Flow?

Ans: Input → Map → Shuffle & Sort → Reduce → Output.

---

Q84. Spark RDD?

Ans: Resilient Distributed Dataset; immutable, distributed collection.

---

Q85. Spark DataFrame?

Ans: Schema-aware, optimized distributed collection of data.

---

Q86. Spark Transformation vs Action?

Ans: Transformation → lazy operations (map, filter); Action → triggers execution (count, collect).

---

Q87. What is Edge Computing?

Ans: Processing near the data source to reduce latency.

---

Q88. Fog Computing?

Ans: Intermediate layer between edge devices and cloud for distributed processing.

---

Q89. Cloud Deployment Models?

Ans: Public, Private, Hybrid, Community.

---

Q90. Cloud Service Models?

Ans: IaaS, PaaS, SaaS.

---

Q91. Multi-Tenancy in Cloud?

Ans: Single software instance serves multiple users with logical separation.

---

Q92. Advantages of Cloud Computing?

Ans: Scalability, cost-efficiency, accessibility, high availability.

---

Q93. Disadvantages of Cloud Computing?

Ans: Security concerns, downtime, limited control, internet dependency.

---

Q94. Agile vs Waterfall?

Ans: Agile → Iterative & flexible; Waterfall → Linear & rigid.

---

Q95. Scrum Roles?

Ans: Product Owner, Scrum Master, Development Team.

---

Q96. Scrum Artifacts?

Ans: Product Backlog, Sprint Backlog, Increment.

---

Q97. Scrum Ceremonies?

Ans: Sprint Planning, Daily Standup, Sprint Review, Sprint Retrospective.

---

Q98. Software Testing Types?

Ans: Unit, Integration, System, Regression, Load, Stress, Performance.

---

Q99. Difference between Black Box and White Box Testing?

Ans: Black Box → Focus on input/output.
White Box → Focus on internal code and logic.

---

Q100. Regression Testing?

Ans: Re-testing after modifications to ensure existing functionality remains intact.

🎓 MCA Semester-4 – Q101 to Q150

---

Q101. What is Load Balancing in Cloud?

Ans: Distributing workloads across multiple servers to ensure high availability and performance.

---

Q102. Types of Load Balancing?

Ans: Round Robin, Least Connections, IP Hash, Weighted Load Balancing.

---

Q103. What is SaaS?

Ans: Software as a Service; delivers software applications over the internet.

---

Q104. What is PaaS?

Ans: Platform as a Service; provides a platform for developing, testing, and deploying applications.

---

Q105. What is IaaS?

Ans: Infrastructure as a Service; provides virtualized computing resources over the internet.

---

Q106. What is Docker?

Ans: Containerization platform for packaging applications and dependencies into lightweight containers.

---

Q107. Difference between Docker and Virtual Machines?

Ans: Docker → shares OS kernel, lightweight, fast.
VM → full OS per instance, heavy, slower.

---

Q108. What is Kubernetes?

Ans: Container orchestration platform for deploying, scaling, and managing containerized applications.

---

Q109. Kubernetes Components?

Ans: Master Node (API Server, Scheduler, Controller), Worker Nodes (Kubelet, Kube Proxy, Pods).

---

Q110. What is CI/CD?

Ans: Continuous Integration/Continuous Deployment; automates code integration, testing, and deployment.

---

Q111. Benefits of CI/CD?

Ans: Faster delivery, fewer errors, consistent deployment, rapid feedback.

---

Q112. Version Control System (VCS)?

Ans: Tool to manage code changes; examples: Git, SVN.

---

Q113. Git vs SVN?

Ans: Git → Distributed, faster, branch-friendly.
SVN → Centralized, slower, simpler.

---

Q114. Git Commands: git clone, git commit, git push?

Ans:

• git clone → copies repo.

• git commit → save changes locally.

• git push → upload changes to remote repo.

---

Q115. What is REST API?

Ans: Architectural style for designing networked applications using HTTP methods.

---

Q116. HTTP Methods in REST?

Ans: GET, POST, PUT, DELETE, PATCH, OPTIONS.

---

Q117. Status Codes in REST API?

Ans: 200 OK, 201 Created, 400 Bad Request, 401 Unauthorized, 404 Not Found, 500 Internal Server Error.

---

Q118. Difference between Stateless and Stateful Services?

Ans: Stateless → no client context; Stateful → maintains client context.

---

Q119. JWT in REST API?

Ans: JSON Web Token; used for stateless authentication and secure data transfer.

---

Q120. OAuth2 in REST API?

Ans: Authorization framework allowing third-party apps to access resources securely.

---

Q121. Big Data Analytics?

Ans: Process of analyzing massive datasets to find patterns, insights, and trends.

---

Q122. Batch Processing vs Stream Processing?

Ans: Batch → processes large datasets at intervals.
Stream → real-time, continuous data processing.

---

Q123. Hadoop vs Spark?

Ans: Hadoop → disk-based batch processing.
Spark → in-memory, fast, supports batch & real-time.

---

Q124. HDFS Features?

Ans: Distributed, fault-tolerant, block storage, scalable.

---

Q125. HDFS Block Size?

Ans: Default 128MB per block; configurable.

---

Q126. Replication Factor in HDFS?

Ans: Default 3; ensures fault tolerance.

---

Q127. NameNode vs DataNode in HDFS?

Ans: NameNode → manages metadata; DataNode → stores actual blocks.

---

Q128. MapReduce Concept?

Ans: Parallel processing using Mapper and Reducer functions on distributed data.

---

Q129. MapReduce Job Flow?

Ans: Input → Map → Shuffle & Sort → Reduce → Output.

---

Q130. Spark RDD?

Ans: Resilient Distributed Dataset; immutable, partitioned collection.

---

Q131. Transformations in Spark?

Ans: map(), filter(), flatMap(), groupByKey(), reduceByKey().

---

Q132. Actions in Spark?

Ans: count(), collect(), reduce(), saveAsTextFile(), take().

---

Q133. Spark DataFrame?

Ans: Schema-aware, optimized distributed collection for structured data.

---

Q134. Difference between DataFrame and RDD?

Ans: DataFrame → high-level, schema-aware, optimized; RDD → low-level, untyped.

---

Q135. Edge vs Cloud Computing?

Ans: Edge → near data source, low latency.
Cloud → centralized, scalable.

---

Q136. Fog Computing?

Ans: Intermediate layer between edge devices and cloud for distributed processing.

---

Q137. Cloud Deployment Models?

Ans: Public, Private, Hybrid, Community.

---

Q138. Cloud Service Models?

Ans: IaaS, PaaS, SaaS.

---

Q139. Multi-Tenancy in Cloud?

Ans: Single software instance serves multiple users with logical separation.

---

Q140. Advantages of Cloud Computing?

Ans: Scalability, cost-efficiency, accessibility, high availability.

---

Q141. Disadvantages of Cloud Computing?

Ans: Security risks, downtime, limited control, internet dependency.

---

Q142. Agile Methodology?

Ans: Iterative approach emphasizing collaboration and working software.

---

Q143. Scrum Roles?

Ans: Product Owner, Scrum Master, Development Team.

---

Q144. Scrum Artifacts?

Ans: Product Backlog, Sprint Backlog, Increment.

---

Q145. Scrum Ceremonies?

Ans: Sprint Planning, Daily Standup, Sprint Review, Sprint Retrospective.

---

Q146. Software Testing Types?

Ans: Unit, Integration, System, Regression, Load, Stress, Performance.

---

Q147. Black Box vs White Box Testing?

Ans: Black Box → focus on input/output; White Box → focus on internal logic and code.

---

Q148. Regression Testing?

Ans: Re-testing after modifications to ensure existing functionality remains intact.

---

Q149. Difference between Functional and Non-Functional Testing?

Ans: Functional → verifies features; Non-Functional → evaluates performance, reliability, usability, security.

---

Q150. What is CI/CD Pipeline?

Ans: Automated process for integrating code, testing, and deploying applications continuously.

🎓 MCA Semester-4 – Q151 to Q200

---

Q151. What is Software Requirement Specification (SRS)?

Ans: Document describing functional and non-functional requirements of software.

---

Q152. Difference between Functional and Non-Functional Requirements?

Ans:

• Functional → Defines what system should do.

• Non-Functional → Defines how system performs (performance, usability, security).

---

Q153. What is Use Case Diagram?

Ans: UML diagram showing interactions between actors and system functionalities.

---

Q154. What is Class Diagram?

Ans: UML diagram representing classes, attributes, methods, and relationships.

---

Q155. What is Sequence Diagram?

Ans: UML diagram showing object interactions over time.

---

Q156. What is Activity Diagram?

Ans: UML diagram showing workflow of activities in system.

---

Q157. Difference between Waterfall and Agile Models?

Ans:

• Waterfall → Linear, sequential.

• Agile → Iterative, incremental, flexible.

---

Q158. What is RAD Model?

Ans: Rapid Application Development; iterative development with prototyping.

---

Q159. What is Spiral Model?

Ans: Iterative model emphasizing risk analysis at each phase.

---

Q160. What is V-Model?

Ans: Extension of Waterfall; testing is planned in parallel with development.

---

Q161. What is SDLC?

Ans: Software Development Life Cycle; process of planning, creating, testing, deploying software.

---

Q162. Phases of SDLC?

Ans: Requirement Analysis → Design → Implementation → Testing → Deployment → Maintenance.

---

Q163. What is Agile Manifesto?

Ans: Principles emphasizing individuals and interactions, working software, customer collaboration, and responding to change.

---

Q164. What is Scrum Master?

Ans: Facilitates Scrum process, removes impediments, ensures team follows Agile practices.

---

Q165. Product Owner Role?

Ans: Represents stakeholders, manages product backlog, prioritizes requirements.

---

Q166. What is Sprint?

Ans: Time-boxed iteration in Agile for delivering a working increment of software.

---

Q167. What is Daily Standup?

Ans: Short daily meeting to track progress, plan tasks, and identify impediments.

---

Q168. What is Sprint Review?

Ans: Meeting to demonstrate completed work to stakeholders.

---

Q169. What is Sprint Retrospective?

Ans: Meeting to reflect on the sprint and identify process improvements.

---

Q170. What is Version Control System (VCS)?

Ans: Tool to manage code changes; e.g., Git, SVN.

---

Q171. Git vs SVN?

Ans: Git → Distributed, fast, branch-friendly; SVN → Centralized, simple.

---

Q172. Git Commands: git commit, git push, git pull?

Ans:

• git commit → Save changes locally.

• git push → Upload changes to remote repo.

• git pull → Fetch and merge changes from remote repo.

---

Q173. What is Continuous Integration (CI)?

Ans: Practice of frequently integrating code into a shared repository.

---

Q174. What is Continuous Deployment (CD)?

Ans: Automated deployment of code to production after passing tests.

---

Q175. What is Docker?

Ans: Containerization platform for packaging apps and dependencies into lightweight containers.

---

Q176. Difference between Docker and VM?

Ans: Docker → lightweight, shares OS; VM → full OS per instance, heavier.

---

Q177. What is Kubernetes?

Ans: Container orchestration platform for deploying, scaling, and managing containers.

---

Q178. Kubernetes Components?

Ans: Master Node (API Server, Scheduler, Controller), Worker Nodes (Kubelet, Kube Proxy, Pods).

---

Q179. What is REST API?

Ans: Architectural style for building web services using HTTP methods.

---

Q180. HTTP Methods?

Ans: GET, POST, PUT, DELETE, PATCH, OPTIONS.

---

Q181. HTTP Status Codes?

Ans: 200 OK, 201 Created, 400 Bad Request, 401 Unauthorized, 404 Not Found, 500 Internal Server Error.

---

Q182. What is JWT?

Ans: JSON Web Token; used for stateless authentication in web services.

---

Q183. OAuth2 Roles?

Ans: Resource Owner, Client, Authorization Server, Resource Server.

---

Q184. Difference between SOAP and REST?

Ans: SOAP → protocol, XML, rigid; REST → architectural style, JSON/XML, lightweight.

---

Q185. What is Microservices Architecture?

Ans: Applications built as small, independent services communicating via APIs.

---

Q186. Advantages of Microservices?

Ans: Scalability, maintainability, independent deployment, fault isolation.

---

Q187. API Gateway?

Ans: Entry point for clients; handles routing, authentication, and rate-limiting in microservices.

---

Q188. Big Data Definition?

Ans: Large datasets that cannot be processed using traditional methods.

---

Q189. 5 Vs of Big Data?

Ans: Volume, Velocity, Variety, Veracity, Value.

---

Q190. Hadoop Ecosystem Components?

Ans: HDFS, MapReduce, YARN, Hive, Pig, HBase, Sqoop, Flume, Oozie.

---

Q191. HDFS Features?

Ans: Distributed, fault-tolerant, block storage, scalable.

---

Q192. HDFS Block Size?

Ans: Default 128MB per block; configurable.

---

Q193. Replication Factor in HDFS?

Ans: Default 3; ensures fault tolerance.

---

Q194. NameNode vs DataNode?

Ans: NameNode → metadata; DataNode → stores actual blocks.

---

Q195. MapReduce Concept?

Ans: Programming model for distributed parallel processing.

---

Q196. MapReduce Job Flow?

Ans: Input → Map → Shuffle & Sort → Reduce → Output.

---

Q197. Spark Features?

Ans: In-memory processing, RDDs, batch & real-time analytics.

---

Q198. RDD in Spark?

Ans: Resilient Distributed Dataset; immutable, partitioned collection.

---

Q199. Spark Transformations vs Actions?

Ans: Transformations → lazy operations (map, filter); Actions → triggers execution (count, collect).

---

Q200. DataFrame in Spark?

Ans: Schema-aware, optimized distributed collection for structured data.

🎓 MCA Semester-4 – Q201 to Q250

---

Q201. What is Edge Computing?

Ans: Processing data near the data source to reduce latency and bandwidth usage.

---

Q202. Difference between Edge and Fog Computing?

Ans: Edge → processing at data source; Fog → intermediate layer between edge and cloud.

---

Q203. Cloud Deployment Models?

Ans: Public, Private, Hybrid, Community.

---

Q204. Cloud Service Models?

Ans: IaaS, PaaS, SaaS.

---

Q205. Multi-Tenancy in Cloud?

Ans: Single software instance serves multiple users with logical separation.

---

Q206. Advantages of Cloud Computing?

Ans: Scalability, cost efficiency, high availability, accessibility.

---

Q207. Disadvantages of Cloud Computing?

Ans: Security risks, downtime, limited control, internet dependency.

---

Q208. What is Virtualization?

Ans: Creating virtual instances of hardware for efficient resource utilization.

---

Q209. Hypervisor Types?

Ans: Type-1 → Bare-metal; Type-2 → Hosted.

---

Q210. Continuous Integration (CI)?

Ans: Practice of frequently integrating code into a shared repository with automated tests.

---

Q211. Continuous Deployment (CD)?

Ans: Automatic deployment of code to production after passing tests.

---

Q212. What is Docker?

Ans: Containerization platform packaging applications and dependencies into lightweight containers.

---

Q213. Docker vs Virtual Machines?

Ans: Docker → shares OS kernel, lightweight; VM → full OS, heavier.

---

Q214. What is Kubernetes?

Ans: Container orchestration platform for deployment, scaling, and management of containers.

---

Q215. Kubernetes Components?

Ans: Master Node → API Server, Scheduler, Controller Manager; Worker Nodes → Kubelet, Kube Proxy, Pods.

---

Q216. What is RESTful Web Service?

Ans: Web service following REST principles using HTTP methods for CRUD operations.

---

Q217. HTTP Methods in REST?

Ans: GET, POST, PUT, DELETE, PATCH, OPTIONS.

---

Q218. Status Codes in REST?

Ans: 200 OK, 201 Created, 400 Bad Request, 401 Unauthorized, 404 Not Found, 500 Internal Server Error.

---

Q219. What is JWT?

Ans: JSON Web Token for stateless authentication and secure data transfer.

---

Q220. OAuth2 Roles?

Ans: Resource Owner, Client, Authorization Server, Resource Server.

---

Q221. Difference between SOAP and REST?

Ans: SOAP → Protocol, XML-based, rigid; REST → Architectural style, JSON/XML, lightweight.

---

Q222. What is Microservices Architecture?

Ans: Application design where services are small, independent, and communicate via APIs.

---

Q223. Advantages of Microservices?

Ans: Scalability, maintainability, independent deployment, fault isolation.

---

Q224. What is API Gateway?

Ans: Entry point for clients; handles routing, authentication, and rate-limiting.

---

Q225. What is Big Data?

Ans: Extremely large datasets that require special techniques for storage and processing.

---

Q226. 5 Vs of Big Data?

Ans: Volume, Velocity, Variety, Veracity, Value.

---

Q227. Hadoop Ecosystem Components?

Ans: HDFS, MapReduce, YARN, Hive, Pig, HBase, Sqoop, Flume, Oozie.

---

Q228. Features of HDFS?

Ans: Distributed, fault-tolerant, block-based storage, scalable.

---

Q229. HDFS Block Size?

Ans: Default 128MB per block; configurable.

---

Q230. Replication Factor in HDFS?

Ans: Default 3; ensures fault tolerance.

---

Q231. NameNode vs DataNode in HDFS?

Ans: NameNode → metadata; DataNode → stores actual data blocks.

---

Q232. MapReduce Concept?

Ans: Parallel processing using Mapper and Reducer functions on distributed datasets.

---

Q233. MapReduce Job Flow?

Ans: Input → Map → Shuffle & Sort → Reduce → Output.

---

Q234. Spark Features?

Ans: In-memory processing, RDDs, batch & real-time analytics.

---

Q235. What is RDD in Spark?

Ans: Resilient Distributed Dataset; immutable, partitioned collection.

---

Q236. Spark Transformations?

Ans: map(), filter(), flatMap(), groupByKey(), reduceByKey().

---

Q237. Spark Actions?

Ans: count(), collect(), reduce(), saveAsTextFile(), take().

---

Q238. DataFrame in Spark?

Ans: Schema-aware, optimized distributed collection for structured data.

---

Q239. DataFrame vs RDD?

Ans: DataFrame → high-level, schema-aware; RDD → low-level, untyped.

---

Q240. Batch Processing vs Stream Processing?

Ans: Batch → processes large datasets at intervals; Stream → real-time continuous processing.

---

Q241. Edge vs Cloud Computing?

Ans: Edge → near data source, low latency; Cloud → centralized, scalable.

---

Q242. Fog Computing?

Ans: Intermediate layer between edge devices and cloud for distributed processing.

---

Q243. Agile Methodology?

Ans: Iterative approach emphasizing collaboration, working software, and customer feedback.

---

Q244. Scrum Roles?

Ans: Product Owner, Scrum Master, Development Team.

---

Q245. Scrum Artifacts?

Ans: Product Backlog, Sprint Backlog, Increment.

---

Q246. Scrum Ceremonies?

Ans: Sprint Planning, Daily Standup, Sprint Review, Sprint Retrospective.

---

Q247. Software Testing Types?

Ans: Unit, Integration, System, Regression, Load, Stress, Performance.

---

Q248. Black Box Testing?

Ans: Testing without knowledge of internal code; focuses on input/output.

---

Q249. White Box Testing?

Ans: Testing with knowledge of internal code; focuses on logic, paths, and coverage.

---

Q250. Regression Testing?

Ans: Re-testing after code changes to ensure existing functionality is intact.

🎓 MCA Semester-4 – Q251 to Q300

---

Q251. What is Software Maintenance?

Ans: Activities to modify and update software after delivery to fix defects, improve performance, or adapt to changes.

---

Q252. Types of Software Maintenance?

Ans: Corrective, Adaptive, Perfective, Preventive.

---

Q253. What is Corrective Maintenance?

Ans: Fixing defects discovered after delivery.

---

Q254. What is Adaptive Maintenance?

Ans: Modifying software to work in a changed environment (OS, hardware, platform).

---

Q255. What is Perfective Maintenance?

Ans: Enhancing features or performance based on user feedback.

---

Q256. What is Preventive Maintenance?

Ans: Modifications to prevent future problems and improve maintainability.

---

Q257. What is Software Reliability?

Ans: Probability that software will function without failure under specified conditions.

---

Q258. What is Software Quality?

Ans: Degree to which software meets specified requirements and customer expectations.

---

Q259. Software Metrics?

Ans: Measures for software processes or products (e.g., LOC, cyclomatic complexity, defect density).

---

Q260. What is Cyclomatic Complexity?

Ans: Metric to measure complexity of a program based on number of independent paths.

---

Q261. What is Defect Density?

Ans: Number of defects per unit size of software (e.g., per KLOC).

---

Q262. What is Load Balancing?

Ans: Distributing workloads across multiple servers to ensure high availability and performance.

---

Q263. Types of Load Balancing?

Ans: Round Robin, Least Connections, IP Hash, Weighted Load Balancing.

---

Q264. What is Docker?

Ans: Containerization platform to package applications with dependencies into lightweight containers.

---

Q265. Difference between Docker and Virtual Machines?

Ans: Docker → shares OS, lightweight; VM → full OS per instance, heavier.

---

Q266. What is Kubernetes?

Ans: Container orchestration platform for deploying, scaling, and managing containers.

---

Q267. Kubernetes Components?

Ans: Master Node → API Server, Scheduler, Controller Manager; Worker Nodes → Kubelet, Kube Proxy, Pods.

---

Q268. Continuous Integration (CI)?

Ans: Practice of frequently integrating code into a shared repository with automated tests.

---

Q269. Continuous Deployment (CD)?

Ans: Automated deployment of code to production after passing tests.

---

Q270. What is REST API?

Ans: Architectural style for web services using HTTP methods for CRUD operations.

---

Q271. HTTP Methods?

Ans: GET, POST, PUT, DELETE, PATCH, OPTIONS.

---

Q272. HTTP Status Codes?

Ans: 200 OK, 201 Created, 400 Bad Request, 401 Unauthorized, 404 Not Found, 500 Internal Server Error.

---

Q273. What is JWT?

Ans: JSON Web Token for stateless authentication in web services.

---

Q274. OAuth2 Roles?

Ans: Resource Owner, Client, Authorization Server, Resource Server.

---

Q275. Difference between SOAP and REST?

Ans: SOAP → protocol, XML-based, rigid; REST → architectural style, lightweight, JSON/XML.

---

Q276. What is Microservices Architecture?

Ans: Applications built as small, independent services communicating via APIs.

---

Q277. Advantages of Microservices?

Ans: Scalability, maintainability, independent deployment, fault isolation.

---

Q278. What is API Gateway?

Ans: Entry point for client requests; handles routing, authentication, and rate-limiting.

---

Q279. What is Big Data?

Ans: Extremely large datasets that cannot be handled by traditional systems.

---

Q280. 5 Vs of Big Data?

Ans: Volume, Velocity, Variety, Veracity, Value.

---

Q281. Hadoop Ecosystem Components?

Ans: HDFS, MapReduce, YARN, Hive, Pig, HBase, Sqoop, Flume, Oozie.

---

Q282. HDFS Features?

Ans: Distributed, fault-tolerant, scalable, block-based storage.

---

Q283. HDFS Block Size?

Ans: Default 128MB; configurable.

---

Q284. Replication Factor in HDFS?

Ans: Default 3; ensures fault tolerance.

---

Q285. NameNode vs DataNode?

Ans: NameNode → metadata; DataNode → stores actual data blocks.

---

Q286. MapReduce Concept?

Ans: Parallel processing using Mapper and Reducer functions on distributed datasets.

---

Q287. MapReduce Job Flow?

Ans: Input → Map → Shuffle & Sort → Reduce → Output.

---

Q288. Spark Features?

Ans: In-memory processing, RDDs, batch & real-time analytics.

---

Q289. RDD in Spark?

Ans: Resilient Distributed Dataset; immutable, partitioned collection.

---

Q290. Transformations in Spark?

Ans: map(), filter(), flatMap(), groupByKey(), reduceByKey().

---

Q291. Actions in Spark?

Ans: count(), collect(), reduce(), saveAsTextFile(), take().

---

Q292. DataFrame in Spark?

Ans: Schema-aware, optimized distributed collection for structured data.

---

Q293. DataFrame vs RDD?

Ans: DataFrame → high-level, schema-aware; RDD → low-level, untyped.

---

Q294. Batch vs Stream Processing?

Ans: Batch → processes large datasets periodically; Stream → real-time, continuous processing.

---

Q295. Edge Computing?

Ans: Processing near data source to reduce latency.

---

Q296. Fog Computing?

Ans: Intermediate layer between edge devices and cloud for distributed processing.

---

Q297. Agile Methodology?

Ans: Iterative approach emphasizing collaboration, working software, and customer feedback.

---

Q298. Scrum Roles?

Ans: Product Owner, Scrum Master, Development Team.

---

Q299. Scrum Artifacts?

Ans: Product Backlog, Sprint Backlog, Increment.

---

Q300. Scrum Ceremonies?

Ans: Sprint Planning, Daily Standup, Sprint Review, Sprint Retrospective.

🎓 MCA Semester-4 – Q301 to Q350

---

Q301. What is Network Topology?

Ans: Physical or logical arrangement of network devices and connections (e.g., Star, Bus, Ring, Mesh).

---

Q302. Types of Network Topologies?

Ans: Star, Bus, Ring, Mesh, Tree, Hybrid.

---

Q303. What is OSI Model?

Ans: 7-layer model standardizing network communication: Physical, Data Link, Network, Transport, Session, Presentation, Application.

---

Q304. What is TCP/IP Model?

Ans: 4-layer model: Link, Internet, Transport, Application.

---

Q305. Difference between OSI and TCP/IP?

Ans: OSI → 7 layers, theoretical; TCP/IP → 4 layers, practical & widely used.

---

Q306. What is IP Address?

Ans: Unique identifier for a device on a network (IPv4/IPv6).

---

Q307. Difference between IPv4 and IPv6?

Ans: IPv4 → 32-bit, dotted decimal; IPv6 → 128-bit, hexadecimal.

---

Q308. What is Subnetting?

Ans: Dividing a network into smaller subnetworks for efficient IP management.

---

Q309. What is DNS?

Ans: Domain Name System; translates domain names to IP addresses.

---

Q310. What is DHCP?

Ans: Dynamic Host Configuration Protocol; automatically assigns IP addresses to devices.

---

Q311. What is HTTP?

Ans: Hypertext Transfer Protocol; protocol for transferring web pages.

---

Q312. What is HTTPS?

Ans: Secure HTTP using SSL/TLS for encrypted communication.

---

Q313. What is SSL/TLS?

Ans: Protocols providing secure data transmission over the internet.

---

Q314. What is Firewall?

Ans: Network security device controlling incoming and outgoing traffic based on rules.

---

Q315. Types of Firewalls?

Ans: Packet-filtering, Stateful Inspection, Proxy, Next-Generation Firewall.

---

Q316. What is VPN?

Ans: Virtual Private Network; secure encrypted connection over the internet.

---

Q317. Types of VPN?

Ans: Remote Access VPN, Site-to-Site VPN.

---

Q318. What is Cloud Security?

Ans: Policies, technologies, and controls to protect data, applications, and infrastructure in the cloud.

---

Q319. Types of Cloud Security Threats?

Ans: Data breaches, account hijacking, insecure APIs, insider threats.

---

Q320. What is Network Latency?

Ans: Delay between sending and receiving data across a network.

---

Q321. Bandwidth vs Throughput?

Ans: Bandwidth → max capacity; Throughput → actual data transmitted.

---

Q322. What is Packet Switching?

Ans: Data divided into packets and transmitted independently across a network.

---

Q323. Circuit Switching?

Ans: Dedicated communication path established for the duration of a session.

---

Q324. Difference between TCP and UDP?

Ans: TCP → connection-oriented, reliable; UDP → connectionless, faster, unreliable.

---

Q325. What is Routing?

Ans: Process of selecting paths for data to travel across a network.

---

Q326. Types of Routing?

Ans: Static Routing, Dynamic Routing.

---

Q327. What is NAT?

Ans: Network Address Translation; maps private IP addresses to public IP addresses.

---

Q328. What is Proxy Server?

Ans: Intermediary server forwarding requests between clients and destination servers.

---

Q329. What is Network Address Translation (NAT)?

Ans: Technique to remap one IP address space into another.

---

Q330. Types of NAT?

Ans: Static NAT, Dynamic NAT, PAT (Port Address Translation).

---

Q331. What is Software Engineering?

Ans: Systematic approach to design, develop, test, and maintain software.

---

Q332. Phases of SDLC?

Ans: Requirement Analysis → Design → Implementation → Testing → Deployment → Maintenance.

---

Q333. What is Requirement Analysis?

Ans: Gathering and analyzing user requirements to define system functionality.

---

Q334. Functional vs Non-Functional Requirements?

Ans: Functional → defines system actions; Non-Functional → defines system attributes.

---

Q335. What is Software Design?

Ans: Process of defining architecture, components, and interfaces of software.

---

Q336. What is Object-Oriented Design?

Ans: Design based on classes, objects, inheritance, and encapsulation.

---

Q337. What is UML?

Ans: Unified Modeling Language; visualizes system design through diagrams.

---

Q338. Types of UML Diagrams?

Ans: Structural (Class, Object), Behavioral (Sequence, Activity, Use Case).

---

Q339. What is Use Case Diagram?

Ans: Diagram showing interactions between actors and system functionalities.

---

Q340. What is Sequence Diagram?

Ans: Diagram showing interactions between objects over time.

---

Q341. What is Activity Diagram?

Ans: Represents workflow of activities within a system.

---

Q342. What is Class Diagram?

Ans: Shows classes, attributes, methods, and relationships.

---

Q343. What is Software Testing?

Ans: Process of evaluating software to identify defects and ensure quality.

---

Q344. Types of Software Testing?

Ans: Unit, Integration, System, Acceptance, Regression, Performance, Load, Stress.

---

Q345. Difference between Black Box and White Box Testing?

Ans: Black Box → tests inputs/outputs; White Box → tests internal logic.

---

Q346. Regression Testing?

Ans: Re-testing software after changes to ensure existing functionality is intact.

---

Q347. Performance Testing?

Ans: Evaluates system performance under load conditions.

---

Q348. Load Testing?

Ans: Checks system behavior under expected peak load.

---

Q349. Stress Testing?

Ans: Checks system behavior under extreme load conditions.

---

Q350. What is Unit Testing?

Ans: Testing individual components or functions in isolation.

🎓 MCA Semester-4 – Q351 to Q400

---

Q351. What is Integration Testing?

Ans: Testing combined modules to verify they work together correctly.

---

Q352. What is System Testing?

Ans: Testing the complete system to ensure it meets specified requirements.

---

Q353. What is Acceptance Testing?

Ans: Testing conducted to determine if the system satisfies user needs.

---

Q354. What is White Box Testing?

Ans: Testing based on internal logic and code structure.

---

Q355. What is Black Box Testing?

Ans: Testing without knowledge of internal code; focuses on inputs and outputs.

---

Q356. Difference between Verification and Validation?

Ans: Verification → ensures product is built correctly.
Validation → ensures correct product is built (meets user requirements).

---

Q357. What is Software Quality Assurance (SQA)?

Ans: Process to ensure software meets quality standards and requirements.

---

Q358. What is Software Configuration Management (SCM)?

Ans: Managing changes to software artifacts and controlling versions.

---

Q359. What is Version Control System (VCS)?

Ans: Tool for managing code changes; examples: Git, SVN.

---

Q360. Git vs SVN?

Ans: Git → distributed, branch-friendly; SVN → centralized, simpler.

---

Q361. What is Git Commit?

Ans: Saves changes locally in Git repository.

---

Q362. Git Push?

Ans: Uploads committed changes to remote repository.

---

Q363. Git Pull?

Ans: Fetches and merges changes from remote repository.

---

Q364. Continuous Integration (CI)?

Ans: Frequently integrating code into a shared repository with automated builds/tests.

---

Q365. Continuous Deployment (CD)?

Ans: Automatic deployment to production after passing tests.

---

Q366. What is Docker?

Ans: Containerization platform packaging applications and dependencies.

---

Q367. Difference between Docker and VM?

Ans: Docker → lightweight, shares OS; VM → full OS, heavier.

---

Q368. What is Kubernetes?

Ans: Container orchestration for deploying, scaling, and managing containers.

---

Q369. Kubernetes Components?

Ans: Master Node → API Server, Scheduler, Controller; Worker Nodes → Kubelet, Kube Proxy, Pods.

---

Q370. What is REST API?

Ans: Architectural style using HTTP for CRUD operations.

---

Q371. HTTP Methods in REST?

Ans: GET, POST, PUT, DELETE, PATCH, OPTIONS.

---

Q372. HTTP Status Codes?

Ans: 200 OK, 201 Created, 400 Bad Request, 401 Unauthorized, 404 Not Found, 500 Internal Server Error.

---

Q373. What is JWT?

Ans: JSON Web Token for stateless authentication.

---

Q374. OAuth2 Roles?

Ans: Resource Owner, Client, Authorization Server, Resource Server.

---

Q375. Difference between SOAP and REST?

Ans: SOAP → protocol, XML; REST → architectural style, JSON/XML, lightweight.

---

Q376. What is Microservices Architecture?

Ans: Applications built as small independent services communicating via APIs.

---

Q377. Advantages of Microservices?

Ans: Scalability, maintainability, independent deployment, fault isolation.

---

Q378. What is API Gateway?

Ans: Entry point for client requests; handles routing, authentication, and rate-limiting.

---

Q379. What is Big Data?

Ans: Extremely large datasets that require special processing techniques.

---

Q380. 5 Vs of Big Data?

Ans: Volume, Velocity, Variety, Veracity, Value.

---

Q381. Hadoop Ecosystem Components?

Ans: HDFS, MapReduce, YARN, Hive, Pig, HBase, Sqoop, Flume, Oozie.

---

Q382. Features of HDFS?

Ans: Distributed, fault-tolerant, scalable, block-based storage.

---

Q383. HDFS Block Size?

Ans: Default 128MB; configurable.

---

Q384. Replication Factor in HDFS?

Ans: Default 3; ensures fault tolerance.

---

Q385. NameNode vs DataNode?

Ans: NameNode → metadata; DataNode → stores actual data blocks.

---

Q386. MapReduce Concept?

Ans: Parallel processing using Mapper and Reducer functions.

---

Q387. MapReduce Job Flow?

Ans: Input → Map → Shuffle & Sort → Reduce → Output.

---

Q388. Spark Features?

Ans: In-memory processing, RDDs, batch & real-time analytics.

---

Q389. What is RDD in Spark?

Ans: Resilient Distributed Dataset; immutable, partitioned collection.

---

Q390. Transformations in Spark?

Ans: map(), filter(), flatMap(), groupByKey(), reduceByKey().

---

Q391. Actions in Spark?

Ans: count(), collect(), reduce(), saveAsTextFile(), take().

---

Q392. DataFrame in Spark?

Ans: Schema-aware, optimized distributed collection.

---

Q393. DataFrame vs RDD?

Ans: DataFrame → high-level, schema-aware; RDD → low-level, untyped.

---

Q394. Batch vs Stream Processing?

Ans: Batch → periodic; Stream → real-time, continuous.

---

Q395. Edge Computing?

Ans: Processing near data source to reduce latency.

---

Q396. Fog Computing?

Ans: Intermediate layer between edge devices and cloud.

---

Q397. Agile Methodology?

Ans: Iterative approach emphasizing collaboration and working software.

---

Q398. Scrum Roles?

Ans: Product Owner, Scrum Master, Development Team.

---

Q399. Scrum Artifacts?

Ans: Product Backlog, Sprint Backlog, Increment.

---

Q400. Scrum Ceremonies?

Ans: Sprint Planning, Daily Standup, Sprint Review, Sprint Retrospective.

🎓 MCA Semester-4 – Q401 to Q450

---

Q401. What is Database Indexing?

Ans: Technique to optimize query performance by creating data structures for faster retrieval.

---

Q402. Types of Database Indexes?

Ans: Primary, Secondary, Unique, Composite, Clustered, Non-Clustered.

---

Q403. What is Normalization?

Ans: Process of organizing database to reduce redundancy and improve data integrity.

---

Q404. Normal Forms?

Ans: 1NF, 2NF, 3NF, BCNF, 4NF, 5NF.

---

Q405. What is Denormalization?

Ans: Combining tables to improve query performance at the cost of redundancy.

---

Q406. ACID Properties in DBMS?

Ans: Atomicity, Consistency, Isolation, Durability.

---

Q407. What is Transaction in DBMS?

Ans: Sequence of operations treated as a single unit of work.

---

Q408. What is Concurrency Control?

Ans: Mechanism to manage simultaneous database operations to prevent conflicts.

---

Q409. What is Deadlock?

Ans: Situation where two or more transactions are waiting indefinitely for resources held by each other.

---

Q410. Methods to Prevent Deadlock?

Ans: Wait-die, Wound-wait, Resource ordering, Deadlock detection & recovery.

---

Q411. What is Hibernate?

Ans: Java ORM framework mapping Java objects to database tables.

---

Q412. Hibernate Features?

Ans: Object-relational mapping, HQL, caching, lazy loading, transaction management.

---

Q413. What is HQL?

Ans: Hibernate Query Language; object-oriented query language for database operations.

---

Q414. Difference between HQL and SQL?

Ans: HQL → operates on objects; SQL → operates on tables.

---

Q415. What is Lazy Loading?

Ans: Fetching related data only when it’s accessed, not immediately.

---

Q416. What is Eager Loading?

Ans: Fetching all related data immediately with the main entity.

---

Q417. Hibernate Caching Types?

Ans: First-level (session), Second-level (session factory), Query cache.

---

Q418. What is Spring Framework?

Ans: Java framework for building enterprise applications using IoC and AOP principles.

---

Q419. What is Dependency Injection (DI)?

Ans: Technique to inject objects into a class rather than creating them internally.

---

Q420. Types of DI in Spring?

Ans: Constructor Injection, Setter Injection, Field Injection.

---

Q421. What is Inversion of Control (IoC)?

Ans: Control of object creation and dependency management is transferred from the class to the framework.

---

Q422. What is Spring Bean?

Ans: Object managed by the Spring container.

---

Q423. Bean Scopes in Spring?

Ans: Singleton, Prototype, Request, Session, GlobalSession, Application.

---

Q424. What is AOP in Spring?

Ans: Aspect-Oriented Programming; separates cross-cutting concerns like logging and security.

---

Q425. AOP Terminology?

Ans: Aspect, Advice, Join Point, Pointcut, Weaving.

---

Q426. What is Spring MVC?

Ans: Model-View-Controller framework in Spring for building web applications.

---

Q427. Components of Spring MVC?

Ans: DispatcherServlet, Controller, Model, ViewResolver, View.

---

Q428. What is REST Controller in Spring?

Ans: @RestController annotation defines a controller that returns JSON/XML responses.

---

Q429. What is Spring Boot?

Ans: Framework to create standalone Spring applications with minimal configuration.

---

Q430. Advantages of Spring Boot?

Ans: Auto-configuration, embedded server, rapid development, reduced boilerplate code.

---

Q431. What is Cloud Computing?

Ans: On-demand delivery of computing resources over the internet.

---

Q432. Cloud Service Models?

Ans: IaaS, PaaS, SaaS.

---

Q433. Cloud Deployment Models?

Ans: Public, Private, Hybrid, Community.

---

Q434. Advantages of Cloud Computing?

Ans: Scalability, cost efficiency, high availability, accessibility.

---

Q435. Disadvantages of Cloud Computing?

Ans: Security risks, downtime, limited control, internet dependency.

---

Q436. What is Virtualization?

Ans: Creating virtual instances of hardware for efficient resource utilization.

---

Q437. Hypervisor Types?

Ans: Type-1 → Bare-metal; Type-2 → Hosted.

---

Q438. What is Edge Computing?

Ans: Processing data near the data source to reduce latency.

---

Q439. What is Fog Computing?

Ans: Intermediate layer between edge devices and cloud for distributed processing.

---

Q440. What is Agile Methodology?

Ans: Iterative approach emphasizing collaboration, working software, and customer feedback.

---

Q441. Scrum Roles?

Ans: Product Owner, Scrum Master, Development Team.

---

Q442. Scrum Artifacts?

Ans: Product Backlog, Sprint Backlog, Increment.

---

Q443. Scrum Ceremonies?

Ans: Sprint Planning, Daily Standup, Sprint Review, Sprint Retrospective.

---

Q444. Software Testing Types?

Ans: Unit, Integration, System, Acceptance, Regression, Performance, Load, Stress.

---

Q445. What is Black Box Testing?

Ans: Testing without knowledge of internal code; focuses on inputs/outputs.

---

Q446. What is White Box Testing?

Ans: Testing with knowledge of internal code; focuses on logic and paths.

---

Q447. Regression Testing?

Ans: Re-testing software after changes to ensure existing functionality works.

---

Q448. Performance Testing?

Ans: Evaluates system performance under expected load.

---

Q449. Load Testing?

Ans: Tests system behavior under peak expected load.

---

Q450. Stress Testing?

Ans: Tests system behavior under extreme load conditions.

🎓 MCA Semester-4 – Q451 to Q500

---

Q451. What is Unit Testing?

Ans: Testing individual components or functions in isolation to ensure correctness.

---

Q452. What is Integration Testing?

Ans: Testing combined modules to verify they work together correctly.

---

Q453. What is System Testing?

Ans: Testing the complete system to ensure it meets specified requirements.

---

Q454. What is Acceptance Testing?

Ans: Testing conducted to determine if the system satisfies user needs and requirements.

---

Q455. White Box Testing?

Ans: Testing based on internal logic and code structure.

---

Q456. Black Box Testing?

Ans: Testing without knowledge of internal code; focuses on input/output validation.

---

Q457. Difference between Verification and Validation?

Ans: Verification → ensures the product is built correctly.
Validation → ensures the correct product is built.

---

Q458. What is Software Quality Assurance (SQA)?

Ans: Ensuring software meets quality standards through defined processes.

---

Q459. What is Software Configuration Management (SCM)?

Ans: Managing software artifacts and controlling versions systematically.

---

Q460. What is Version Control System (VCS)?

Ans: Tool for managing code changes; examples include Git, SVN.

---

Q461. Git Commit?

Ans: Saves changes locally in Git repository.

---

Q462. Git Push?

Ans: Uploads committed changes to remote repository.

---

Q463. Git Pull?

Ans: Fetches and merges changes from remote repository.

---

Q464. What is Continuous Integration (CI)?

Ans: Practice of frequently integrating code into a shared repository with automated tests.

---

Q465. What is Continuous Deployment (CD)?

Ans: Automatically deploying code to production after successful tests.

---

Q466. What is Docker?

Ans: Containerization platform packaging applications with dependencies.

---

Q467. Docker vs Virtual Machines?

Ans: Docker → lightweight, shares OS kernel; VM → full OS, heavier.

---

Q468. What is Kubernetes?

Ans: Container orchestration platform for deploying, scaling, and managing containers.

---

Q469. Kubernetes Components?

Ans: Master Node → API Server, Scheduler, Controller; Worker Nodes → Kubelet, Kube Proxy, Pods.

---

Q470. What is REST API?

Ans: Architectural style for web services using HTTP for CRUD operations.

---

Q471. HTTP Methods in REST?

Ans: GET, POST, PUT, DELETE, PATCH, OPTIONS.

---

Q472. HTTP Status Codes?

Ans: 200 OK, 201 Created, 400 Bad Request, 401 Unauthorized, 404 Not Found, 500 Internal Server Error.

---

Q473. What is JWT?

Ans: JSON Web Token used for stateless authentication.

---

Q474. OAuth2 Roles?

Ans: Resource Owner, Client, Authorization Server, Resource Server.

---

Q475. Difference between SOAP and REST?

Ans: SOAP → protocol, XML-based; REST → architectural style, JSON/XML, lightweight.

---

Q476. What is Microservices Architecture?

Ans: Application design where services are small, independent, and communicate via APIs.

---

Q477. Advantages of Microservices?

Ans: Scalability, maintainability, independent deployment, fault isolation.

---

Q478. What is API Gateway?

Ans: Entry point for client requests; handles routing, authentication, and rate-limiting.

---

Q479. What is Big Data?

Ans: Extremely large datasets that require special processing techniques.

---

Q480. 5 Vs of Big Data?

Ans: Volume, Velocity, Variety, Veracity, Value.

---

Q481. Hadoop Ecosystem Components?

Ans: HDFS, MapReduce, YARN, Hive, Pig, HBase, Sqoop, Flume, Oozie.

---

Q482. Features of HDFS?

Ans: Distributed, fault-tolerant, scalable, block-based storage.

---

Q483. HDFS Block Size?

Ans: Default 128MB; configurable.

---

Q484. Replication Factor in HDFS?

Ans: Default 3; ensures fault tolerance.

---

Q485. NameNode vs DataNode?

Ans: NameNode → stores metadata; DataNode → stores actual data blocks.

---

Q486. MapReduce Concept?

Ans: Parallel processing model using Mapper and Reducer functions on distributed datasets.

---

Q487. MapReduce Job Flow?

Ans: Input → Map → Shuffle & Sort → Reduce → Output.

---

Q488. Spark Features?

Ans: In-memory processing, RDDs, batch & real-time analytics.

---

Q489. What is RDD in Spark?

Ans: Resilient Distributed Dataset; immutable, partitioned collection.

---

Q490. Transformations in Spark?

Ans: map(), filter(), flatMap(), groupByKey(), reduceByKey().

---

Q491. Actions in Spark?

Ans: count(), collect(), reduce(), saveAsTextFile(), take().

---

Q492. DataFrame in Spark?

Ans: Schema-aware, optimized distributed collection.

---

Q493. DataFrame vs RDD?

Ans: DataFrame → high-level, schema-aware; RDD → low-level, untyped.

---

Q494. Batch vs Stream Processing?

Ans: Batch → periodic; Stream → real-time continuous processing.

---

Q495. Edge Computing?

Ans: Processing near data source to reduce latency.

---

Q496. Fog Computing?

Ans: Intermediate layer between edge devices and cloud for distributed processing.

---

Q497. Agile Methodology?

Ans: Iterative approach emphasizing collaboration, working software, and customer feedback.

---

Q498. Scrum Roles?

Ans: Product Owner, Scrum Master, Development Team.

---

Q499. Scrum Artifacts?

Ans: Product Backlog, Sprint Backlog, Increment.

---

Q500. Scrum Ceremonies?

Ans: Sprint Planning, Daily Standup, Sprint Review, Sprint Retrospective.