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Course Detail

Course Name Data Structures
Course Code 26CSA201
Program 5 Year Integrated B.C.A – M.C.A
Semester 3
Credits 4
Campus Mysuru

Syllabus

Unit I

Introduction and Definition of Data Structure, Classification of Data Structures: Primitive and Non‑primitive data structures. Linear and Non‑linear data structures, Abstract Data Type (ADT). Introduction to implementation issues

Unit II

Enumerated, Structure, and Union Types– The Type Definition (typedef), Enumerated types, Structures –Declaration, initialization, accessing structures, operations on structures, structures, and functions, Passing structures through pointers. Introduction to Union

Unit III

Array ADT, Types of Arrays: 1-D, 2-D, and multi-dimension. Applications of Arrays: Linear Search, Binary Search and its analysis. Sorting: Bubble Sort, Insertion Sort, Selection Sort, and its analysis. Linked List, List as an ADT Types of Linked List, and insertion and deletion operations of linked list: Singly, Circular, and Doubly.

Unit IV

Stacks ADT, Operations on Stack: Push, Pop, and Traversing. Applications of Stack: Expression conversion, Postfix Evaluation, Recursion: Tower of Hanoi, Merge Sort, Quick Sort. Analysis of Recursive Algorithms using Back Substitution and Masters Method. Queue ADT, Operations on Queue: Insertion, Deletion, and Traversing. Circular Queue.

Unit V

Graphs ADT, basic terminologies, types of graphs. Graph Representation: Adjacency Matrix, Incidence Matrix, Adjacency List. Tree ADT, Basic Terminologies, Binary tree properties, Tree Traversal: Pre-order, In-order, and Postorder.

Objectives and Outcomes

Course Objective(s) 

  • Understand the concept and importance of organizing data using appropriate data structures. 
  • Develop the ability to analyze and select suitable data structures for solving computational problems. 
  • Enable students to design and implement abstract data types (ADTs) and their operations. 
  • Build competence in applying linear and non‑linear data structures for problem solving. 

Course Outcomes 

COs 

Description 

CO1 

Analyze data handling requirements and classify problems based on appropriate data structure selection 

CO2 

Design abstract data types (ADTs) and represent data using structured and dynamic data types 

CO3 

Implement linear data structures such as arrays, stacks, queues, and linked lists to solve problems 

CO4 

Apply nonlinear data structures like trees and graphs in computational problem solving 

CO5 

Evaluate the efficiency and suitability of data structures for realworld applications 

CO-PO Mapping 

PO 

PO1 

PO2 

PO3 

PO4 

PO5 

PO6 

PO7 

PO8 

CO 

CO1 

CO2 

CO3 

CO4 

CO5 

Textbooks/ References

Textbooks

  • E. Horowitz & Sahni, Fundamental Data Structure, Galgotia Book Source, 1983.
  • A. Tannenbaum, Data Structure Using C, Pearson Education, 2003.

References

  • Classic Data Structures by D. Samanta, Second Edition.

Evaluation Pattern

Assessment 

Weightage (%) 

Midterm 

25 

Continuous Assessment 

25 

End Semester Exam 

50 

Total Marks 

100 

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