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
| Course Name | Data Structures |
| Course Code | 26CSA201 |
| Program | 5 Year Integrated B.C.A – M.C.A |
| Semester | 3 |
| Credits | 4 |
| Campus | Mysuru |
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
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
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.
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.
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.
Course Objective(s)
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 |
3 |
3 |
2 |
2 |
0 |
0 |
0 |
1 |
|
CO2 |
3 |
2 |
3 |
2 |
0 |
0 |
0 |
1 |
|
CO3 |
3 |
2 |
3 |
2 |
0 |
0 |
0 |
1 |
|
CO4 |
2 |
2 |
3 |
2 |
0 |
0 |
0 |
1 |
|
CO5 |
2 |
3 |
2 |
2 |
0 |
0 |
1 |
2 |
Textbooks
References
|
Assessment |
Weightage (%) |
|
Midterm |
25 |
|
Continuous Assessment |
25 |
|
End Semester Exam |
50 |
|
Total Marks |
100 |
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