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tu design analysis algo - Syllabus | TABFlux

Design and Analysis of Algorithm

Design and Analysis of Algorithms focuses on developing efficient algorithms and evaluating their performance. It covers algorithm design techniques, correctness, and complexity analysis (time and space), enabling learners to choose optimal solutions for solving computational problems effectively.

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Data Structures and Algorithms

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Course Title: Data Structures and Algorithms

Course No: BIT201

Nature of the Course: Theory + Lab

Semester: 3

Full Marks: 60 + 20 + 20

Pass Marks: 24 + 8 + 8

Credit Hours: 3

Course Description

Course Objectives

Course Contents

1. Unit 1: Background and Concept of Data Structures

2 hrs

1.1. Introduction: Data Types, Data Structure, Abstract Data Type

1.2. Background for Data Structure: Array, Array as an ADT, Structure, Pointer, Class in C++

2. Unit 2: Algorithms

2 hrs

2.1. Fundamentals of Algorithm

2.2. Elementary Analysis of algorithm with asymptotic notations and their properties, time and space complexities

3. Unit 3: Stack

4 hrs

3.1. Definition

3.2. Primitive Operations, Stack as an ADT

3.3. Stack Applications: Evaluation of Infix, Postfix and Prefix expressions, converting from infix to postfix

4. Unit 3: Queue (Repeated Index in Original)

3 hrs

4.1. Definition

4.2. Primitive Operations, Queue as an ADT

4.3. Circular and Priority Queues

5. Unit 4: Recursion

2 hrs

5.1. Definition and Principle

5.2. Application of recursion with TOH problem, Factorial, Fibonacci Sequences

6. Unit 5: List

9 hrs

6.1. Definition, Static and Dynamic List Structure

6.2. Operations on Linked List

6.3. Linked implementation of a stack

6.4. Linked implementation of a queue

6.5. Circular Linked List

6.6. Doubly Linked List

6.7. Doubly Circular Linked List

7. Unit 6: Tree

7 hrs

7.1. Definition and basic terminologies

7.2. Binary Tree: Introduction, Types of Binary Tree, Operations

7.3. Binary Search Tree: Insertion, Deletion, Searching

7.4. Tree Traversal: Pre-order traversal, In-order traversal, Post-order traversal

7.5. Applications of Binary Tree

8. Unit 7: Sorting

6 hrs

8.1. Introduction and types of sorting

8.2. Algorithm and implementation of Bubble Sort, Insertion Sort, Selection Sort, Quick Sort, Merge Sort

8.3. Comparison and Efficiency of sorting algorithms

9. Unit 8: Searching

5 hrs

9.1. Introduction

9.2. Sequential Search, Binary Search and Tree Search

9.3. Comparison and Efficiency of Searching

10. Unit 9: Graph

5 hrs

10.1. Definition, Representation of Graph, Types of Graph

10.2. Graph Traversal: Depth First Search, Breadth First Search

10.3. Spanning Tree, Prim’s Algorithm, Kruskal’s algorithm and Round Robin Algorithm

10.4. Shortest Path Algorithm, Greedy and Dijkstra’s Algorithm

Laboratory Works

1.Implementation of Stack
2.Implementation of Queue
3.Implementation of Lists
4.Implementation of Tree
5.Implementation of Graphs
6.Implementation of Recursive functions
7.Implementation of Sorting Algorithms
8.Implementation of Searching Algorithms

Text Books

1.Data structure using C and C++, Langsam, Augenstein, Tenenbaum

Reference Books

1.Horowitz and Sahni, Fundamentals of Data Structures
2.Aho, Hopcroft and Ullman, Data Structure and Algorithms

Notes:

Source:

The course familiarizes students with different concepts of data structures, abstract types, and algorithms.

This course aims to provide sufficient theoretical and practical knowledge of data structure and algorithms required to build efficient programs.

Data Structure and Algorithm is highly practical oriented course. Each unit should include plenty of programming practices.

This syllabus follows the official BIT curriculum of Tribhuvan University. In case of any doubt or revision, the university’s published syllabus shall be considered authoritative.