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Course Detail

Course Name Data Structures
Course Code 26CSC201
Semester 3
Credits 4
Campus Coimbatore

Syllabus

Unit 1

Introduction Variables Data types Data structures Abstract Data Type (ADT)- Algorithm Analysis of Algorithm Run time Analysis Rate of Growth Commonly used Rate of Growth Types of Analysis Asymptotic Notations Why Asymptotic Analysis Properties of Notations Master theorem.Recursion and Back tracking Recursion Vs Iteration Problems on Recursion and Back tracking (12 hrs)

Unit 2

Basic ADT- lists Array implementation of Lists Pointer implementation of lists comparison. Elementary Data structures Performance of Basic data structures – Implementation of ADT Stack Application of Stack Conversion of infix to postfix expression- Evaluation of Postfix expression -, Queue, Deqeue Applications Implementation of Queue and Dequeue. (12 hrs)

Unit 3

Linked List Linked List ADT Why Linked List Comparison of Linked list with Arrays and Dynamic Arrays Singly Linked List Operations Doubly Linked List Operations Circular Linked list Operations Applications. (10 hrs)

Unit 4

Trees Terminologies Tree Nodes Binary Trees Types Applications – Traversals N-ary Trees Threaded Binary Trees Binary Search Trees Applications- Balanced Binary Search Tree AVL Trees Priority Queues and Heaps 2-3-4 Trees. Graphs Directed and Undirected Graphs Graph Representation Graph Traversal Articulation Point and Biconnected Components – Transitive Closure-Shortest Paths- Dijkstras, Bellman Ford, FlyodWarshall-Minimum Spanning Tree Kruskal, Prims, Baruvkas. (12 hrs)

Unit 5

Searching and Sorting – Linear Search- Binary Search Sorting Selection- Bubble Insertion Quick Sort Merge sort. Symbol Tables and Hashing Hash Table Hash Functions Collision Collision Resolution techniques. (10 hrs)

Text Books / References

Text Books:

  1. Narasimha Karumanchi, “Data and Algorithms Made Easy”, Career Monk publications, 2023.
  2. Miller and Rannum , “Problem Solving with Algorithms and Data Structures using Python”,
  3. Thomas H.Cormen,CharlesE.Liserson,RonaldD.Rivest,Clifford Steins, Introduction to Algorithms, third edition,MIT Press, 2009
  4. Benjamin Baka, Python Data Structures and Algorithms, Packt Publishing Ltd, 2017.
  5. Ellitz Horowitz, Sarataj Sahini, Senguthevar Rajasekaran, Computer Algorithms, 2ndedition, Silicon Press, 2008.

Reference Books

  1. Alfred V Aho, John E Hopcroft, Jeffrey D Ullman. Data Structures & Algorithms, Pearson Publishers, 2002
  2. Michael T. Goodrich & Roberto Tamassia, Data Structures and Algorithms in Python, Wiley, 2021, 6th edition.

Objectives and Outcomes

CO-PO Mapping

Course Outcomes
CO1 Understand the basic concepts of data and growth functions
CO2 Understand the elements of Data structures and its applications
CO3 Understand linked list and types of linked list, performance and applications
CO4 Understand various types of trees and graph structures with applications
CO5 Understand various types of searching and sorting techniques.

 

PO1

PO2

PO3

PO4

PO5

PO6

PO7

PO8

PO9

PO10

PO11

PO12

CO1

3

3

3

3

3

3

 

 

 

 

 

2

CO2

3

3

3

3

3

3

 

 

 

 

 

2

CO3

3

3

3

3

3

3

 

 

 

 

 

2

CO4

3

3

3

3

3

3

 

 

 

 

 

2

CO5

3

3

3

3

3

3

 

 

 

 

 

2

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