CS25C04 Data Structures and Algorithms – Semester II – EEE – R-2025

Subject Code & Name: CS25C04 – Data Structures and Algorithms

Regulation: R-2025

Semester: II (Second Semester)

Branch: B.E. Electrical and Electronics Engineering (EEE)

Credits / L-T-P: 4 Credits | L-T-P: 3-0-2

Course Objectives

• To provide the fundamentals of data organization and algorithms.

Full Unit-wise Syllabus

Unit I – Data Types

Abstract Data Types (ADTs), ADTs and classes, introduction to OOP, Classes in Python, Inheritance, Namespaces, Shallow and Deep Copying.

Practical: Implement simple ADTs as Python classes

Unit II Linear Structures

List ADT, array-based implementations, linked list implementations, singly linked lists, circularly linked lists, doubly linked lists, Stack ADT, Queue ADT, double ended queues, applications

Practical: List ADT using Python arrays, Linked list, Stack and Queue ADTs and Applications.

Unit III – Tree Structures

Tree ADT, Binary Tree ADT, tree traversals, binary search trees, AVL trees, heaps, multi-way search trees

Practical: Tree representation and traversal algorithms, Binary Search Trees, Heaps.

Unit IV Graph Structures

Graph ADT, representations of graph, graph traversals, DAG, topological ordering, greedy algorithms, dynamic programming, shortest paths, minimum spanning trees, introduction to complexity classes and intractability

Practical: Graph representation and Traversal algorithms, Single source shortest path algorithm, Minimum spanning tree algorithms.

Unit V – Algorithm

Analysis of algorithms, Asymptotic notations, Divide & Conquer, Recursion, Recursive Algorithms

Practical: Implement recursive algorithms in Python.

Unit VI – Sorting and Searching

Bubble sort, Selection sort, Insertion sort, Merge sort, Quick sort, Analysis of sorting algorithms, Linear & Binary search, Hashing, Hash functions, Collision handling, Load factors, Rehashing, and Efficiency

Practical: Sorting and searching algorithms, Hash tables.

Course Outcomes (COs)

• CO1: Explain fundamental concepts of data structures and Algorithms.
• CO2: Implement the data structures in different Applications.
• CO3: Evaluate and compare different searching and sorting algorithms.
• CO4: Demonstrate in continuous learning in interdisciplinary projects involving AI, ML, Data Science, or other technology domains.

Assessment Pattern (Quick Note)

• Weightage: Continuous Assessment 40% | End Semester Examinations 60%
• Internal methodology: Quiz (10%), Assignments (30%) Review of GATE questions (20%) and Internal Examinations (50%)

Source: Official Anna University – B.E. Electrical and Electronics Engineering R-2025 Syllabus
Last Updated: September 2026