Subject Code & Name: CS25C08 – Data Structures
Regulation: R-2025
Semester: III (Third Semester)
Branch: B.E. Computer Science and Engineering (CSE) / B.Tech. Information Technology (IT) / B.Tech. Artificial Intelligence and Data Science (AI&DS) / B.Tech. Computer Science and Business Systems (CSBS) / B.E. Computer and Communication Engineering (CCE) / B.E. Computer Science and Engineering (Data Science) (CSE(DS)) / B.E. Computer Science and Engineering (Internet of Things) (CSE(IoT)) / B.E. Computer Science and Engineering (Cyber Security) (CSE(Cyber)) / B.E. Computer Science and Engineering (Artificial Intelligence and Machine Learning) (CSE(AI&ML)) / B.E. Computer Science and Design (CSD)
Credits / L-T-P: 5 Credits | L-T-P: 3-0-4
Course Objectives
- This course presents various data structures and their importance to provide a comprehensive view about problem solving skills.
Full Unit-wise Syllabus
Unit I – Linear Data Structures
Abstract Data Types – Internal Representation of Primitive Data Structures – One Dimensional and Multi-Dimensional Arrays – linear lists – Singly, doubly, Circular linked lists – Applications.
Practical: Single and Multidimensional arrays; Singly, Doubly and Circular Linked Lists
Unit II – Stacks and Queues
Stack: Representations – Operations – Implementations – Applications. Queue: Representations – Operations – Implementations – Types – Applications.
Practical: String reverse operations and Expression evaluation; Circular Queue and Priority Queue
Unit III – Trees
Representations – Types – Binary Search Trees (BSTs) – AVL Tree – Operations: Search, Traversals, Rotations – Balanced BSTs – Splay trees – B-trees – Binary Heaps.
Practical: Traversal operation; AVL Tree rotations; Query and Update operations on Balanced BSTs
Unit IV – Sorting, Searching & Hashing Techniques
Linear and Binary Search – Bubble Sort – Insertion Sort – Merge Sort – Bucket Sort – Quick Sort – Heap sort – Hashing techniques – Dictionaries – Hash function – Collision – Separate chaining – open addressing.
Practical: Quick and Heap Sort; Binary Search and Hashing
Unit V – Graphs
Representation – Types – Operations – Prim's, Kruskal algorithms – Dijikstra's algorithm – Connected and Biconnected Components.
Practical: BFS and DFS algorithms; Minimum Spanning Tree and shortest path algorithms
Course Outcomes (COs)
- CO1: Describe the concepts and operations of data structures for efficient data organization and manipulation.
- CO2: Analyze data structures to understand their performance and application suitability.
- CO3: Evaluate data structure algorithms in terms of time and space complexity for solving computational problems.
- CO4: Design appropriate data structures and algorithms for real-world problem scenarios.
- CO5: Develop the ability to apply emerging data structures through continuous self-learning and practice.
Assessment Pattern (Quick Note)
- Weightage: Continuous Assessment 50% | End Semester Examinations 50%
- Internal methodology: Activities 10% (Assignments 30, Quiz 10, Project based learning 25, Flipped Classroom 10, Review of GATE questions 25), Internal Theory Examinations 30%, Internal Laboratory Examination 10%
Source: Official Anna University – B.E. Computer Science and Engineering R-2025 Syllabus
Last Updated: September 2026
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