Data Structures and Algorithms(DSA) Syllabus

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This page contains Syllabus of Data Structures and Algorithms of BIT.

Title Data Structures and Algorithms
Short Name DSA
Course code BIT201
Nature of course Theory
Third Semester
Full marks 80 + 20
Pass marks 32 + 8
Credit Hrs 3
Elective/Compulsary Compulsary

Course Description

Course Synopsis: This course contains the concepts of different types of data structures and concepts of algorithms and their analysis.

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

Units and Unit Content

1. Background and Concept of Data Structures
teaching hours: 2 hrs

Concepts of Data Types, Data Structure, Abstract Data Type and their uses Background for Data Structure, Definition and use of ADT, Array as an ADT, Structure, Pointer

2. Algorithms
teaching hours: 2 hrs

Introduction to Algorithm and their properties, Concepts of Analysis of algorithm with asymptotic notations (Big Oh) and their properties, time and space complexities

3. Stack
teaching hours: 4 hrs

Definition and Primitive Operations, Stack as an ADT, Stack Applications: Evaluation of Infix, Postfix and Prefix expressions, converting from infix to prefix and postfix.

4. Queue
teaching hours: 3 hrs

Definition, Queue as an ADT and Primitive Operations of Linear and Circular Queue,  Application and advantages of Linear, Circular Queue, and Priority Queue (Ascending and Descending Priority Queue)

5. Recursion
teaching hours: 2 hrs

Definition and Principle of Recursion, Application of Recursion, Recursion removal using stack, example of recursion for TOH Factorial, Fibonacci Sequences, GCD, efficiency of above recursive algorithms

6. List
teaching hours: 9 hrs

List concepts, Definition and List as ADT, Static and Dynamic List Structure and implementation, Types of linked list, Operations on Linked List, Singly linked list, Circular Linked List, Doubly Linked List, Doubly Circular Linked List, Inserting, traversing and deleting nodes at beginning, end and specified positions in these linked lists, Linked implementation of a stack and queue in singly linked list

7. Tree
teaching hours: 7 hrs

Definition and basic terminologies of tree, Binary Tree: Introduction, Types of Binary Tree, Level and depth, height balance tree(AVL), Operations in Binary Search Tree (BST): Insertion, Deletion, Searching, Tree Traversal: Pre-order traversal , In-order traversal (sorted list of Nodes), Post-order traversal, Applications of Binary Tree (Huff man tree, expression tree)

8. Sorting
teaching hours: 6 hrs

Introduction and types of sorting Algorithm and implementation of Bubble Sort, Insertion Sort, Selection Sort, Quick Sort, Merge Sort Comparison and Efficiency of sorting algorithms

9. Searching
teaching hours: 5 hrs

Introduction Sequential Search, Binary Search and Tree Search Comparison and Efficiency of Searching, Hashing: hash function, hash table and collision resolution techniques 

10. Graph
teaching hours: 5 hrs

Definition, Representation of Graph, Types of Graph, Graph Traversal: Depth First Search, Breadth First Search Spanning Tree, Prim’s Algorithm, Kruskal’s algorithm and Round Robin Algorithm, Shortest Path Algorithm, Greedy and Dijkstra’s Algorithm

Lab and Practical works

Data Structure and Algorithm is highly practical oriented course. Each unit should include plenty of programming practices. Laboratory work should include implementation of Stack, Queue, Lists, Tree, Graphs, and Recursive functions as well as implementation of Sorting Algorithms and Searching Algorithms. Laboratory exercises can be implemented in high level programming languages like C or C++.

Some important contents that should be included in lab exercises are as follows:

• Write a program to implement array as an ADT.

• Writing programs to implement stack operations

• Writing programs using stack to convert infix expression to postfix/prefix expression

• Write a program to evaluate postfix expression using stack

• Writing programs to implement primitive operation in linear and circular queue. 

• Writing recursive programs to implement factorial, Fibonacci sequence, GCD, and Tower of Hanoi algorithms

• Writing programs with dynamic memory allocation and de-allocation

• Writing programs for operation of linear linked list

• Linked list implementation of stack and queue

• Writing programs to implement Binary Search Trees basic operations

• Writing programs to implement sorting algorithms; bubble, insertion, selection, merge and quick sort

• Writing programs to implement: sequential, binary search and hashing

• Writing programs to implement searching, spanning tree and shortest path algorithms in graph