CS3301 Data Structures Previous Year Question Papers - Anna University
Explore the Previous Year Anna University Question Papers of CS3301 Data Structures.
2024
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2024 - CSE-AM-2024-CS 3301-Data Structures -765038315-50896.pdf
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2024 - CSE-ND-2024-CS 3301-Data Structures -866959044-20250604161745 (6).pdf
2023
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2023 - CSE-AM-2023-CS 3301-Data Structures -406991499-AM23C (1).pdf
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2023 - CSE-ND-2023-CS 3301-Data Structures-365448677-20863.pdf
2022
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2022 - CSE-ND-2022-CS 3301-Data Structures -196053558-ND22CS (4).pdf
Important Questions - CS3301 Data Structures
UNIT I: LISTS
Part A (2 Marks)
- Define Abstract Data Type (ADT) with an example.
- Differentiate between Linear and Non-linear data structures.
- Compare Arrays and Linked Lists.
- What are the applications of Linked Lists?
- Define Singly and Doubly Linked List.
Part B (13/15 Marks)
- Explain Singly Linked List operations (insertion, deletion, traversal) with algorithms.
- Describe Doubly Linked List and Circular Linked List with advantages.
- Write an algorithm for Polynomial Addition using Linked Lists.
- Compare Array vs Linked List with suitable examples.
UNIT II: STACKS AND QUEUES
Part A (2 Marks)
- Define Stack and its operations (Push, Pop).
- What is Queue? Mention its types.
- Define Circular Queue and its advantage.
- What is Deque?
- List applications of Stack.
Part B (13/15 Marks)
- Explain Infix to Postfix conversion using Stack with example.
- Evaluate a Postfix expression using Stack.
- Explain Queue implementation using Arrays and Linked Lists.
- Describe applications of Stack (Recursion, Expression Evaluation).
UNIT III: TREES
Part A (2 Marks)
- Define Binary Tree and its types.
- What is Binary Search Tree (BST)?
- Define AVL Tree and Balance Factor.
- List tree traversal methods.
- What is a Binary Heap?
Part B (13/15 Marks)
- Explain BST operations (Insertion, Deletion, Searching) with algorithms.
- Describe AVL Tree rotations (LL, RR, LR, RL) with example.
- Explain Tree Traversals with examples.
- Describe Binary Heap and Priority Queue implementation.
UNIT IV: GRAPHS AND MULTIWAY TREES
Part A (2 Marks)
- Define Graph and its representations.
- What is BFS and DFS?
- Define Minimum Spanning Tree (MST).
- What is Dijkstra's Algorithm?
- Define B-Tree and B+ Tree.
Part B (13/15 Marks)
- Explain BFS and DFS algorithms with example.
- Describe Dijkstra's Algorithm for shortest path.
- Compare Prim's and Kruskal's algorithms.
- Explain B-Tree and B+ Tree structure and operations.
- Explain Topological Sorting with example.
UNIT V: SEARCHING, SORTING AND HASHING
Part A (2 Marks)
- Define Linear Search and Binary Search.
- What is Hashing?
- Define Collision and Rehashing.
- Compare Internal and External Sorting.
- What is Load Factor in Hashing?
Part B (13/15 Marks)
- Explain Sorting Algorithms: Bubble, Selection, Insertion.
- Describe Merge Sort and Quick Sort using Divide and Conquer.
- Explain Binary Search with algorithm.
- Discuss Hashing techniques and Collision Resolution methods.
- Compare different sorting techniques with time complexity.
Most Repeated / High-Weight Questions
Linked list operations, infix to postfix conversion, BST operations and AVL rotations, tree traversals, BFS/DFS algorithms, sorting algorithms with time complexity, hashing collision resolution.
Additional Resources
How to Use These Question Papers
- Unit-Wise Preparation: Complete Unit I-II for foundation, dedicate 50% of time to Unit III-IV (trees, graphs are most frequently asked).
- Algorithm Mastery: Understand and implement BFS, DFS, Dijkstra's, sorting algorithms (Quick Sort, Merge Sort). Write pseudocode first, then trace with examples.
- Time Complexity Analysis: Learn Big-O notation for each algorithm. Compare time and space complexity across different approaches (especially sorting algorithms).
- Tree Operations Practice: BST insertion/deletion and AVL rotations appear in almost every exam. Practice all four rotation cases (LL, RR, LR, RL) with manual tracing.
- Problem Solving Strategy: For each question, identify data structure requirements first, then algorithm, then implement. Practice time-bound problem solving.