Data Structures and Algorithms(DSA) Syllabus

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

Title Data Structures and Algorithms
Short Name DSA
Course code CSC206
Nature of course Theory + Lab
Third Semester
Full marks 60 + 20 + 20
Pass marks 24 + 8 + 8
Credit Hrs 3
Elective/Compulsary Compulsary

Course Description

Course Description:

This course includes the basic foundations in of data structures and algorithms. This course

covers concepts of various data structures like stack, queue, list, tree and graph. Additionally,

the course includes idea of sorting and searching.

Course Objectives:

  •  To introduce data abstraction and data representation in memory
  •  To describe, design and use of elementary data structures such as stack, queue, linked list, tree and graph
  •  To discuss decomposition of complex programming problems into manageable sub problems
  •  To introduce algorithms and their complexity

Units and Unit Content

1. Introduction to Data Structures & Algorithms
teaching hours: 4 hrs

1.1 Data types, Data structure and Abstract date type

1.2 Dynamic memory allocation in C

1.3 Introduction to Algorithms

1.4 Asymptotic notations and common functions

2. Stack
teaching hours: 4 hrs

2.1 Basic Concept of Stack, Stack as an ADT, Stack Operations, Stack Applications

2.2 Conversion from infix to postfix/prefix expression, Evaluation of postfix/ prefix


3. Queue
teaching hours: 4 hrs

3.1 Basic Concept of Queue, Queue as an ADT, Primitive Operations in Queue

3.2 Linear Queue, Circular Queue, Priority Queue, Queue Applications

4. Recursion
teaching hours: 3 hrs

4.1 Principle of Recursion, Comparison between Recursion and Iteration, Tail Recursion

4.2 Factorial, Fibonacci Sequence, GCD, Tower of Hanoi(TOH)

4.3 Applications and Efficiency of Recursion

5. Lists
teaching hours: 8 hrs

5.1 Basic Concept, List and ADT, Array Implementation of Lists, Linked List

5.2 Types of Linked List: Singly Linked List, Doubly Linked List, Circular Linked List.

5.3 Basic operations in Linked List: Node Creation, Node Insertion and Deletion from

Beginning, End and Specified Position

5.4 Stack and Queue as Linked List

6. Sorting
teaching hours: 8 hrs

6.1 Introduction and Types of sorting: Internal and External sort

6.2 Comparison Sorting Algorithms: Bubble, Selection and Insertion Sort, Shell Sort

6.3 Divide and Conquer Sorting: Merge, Quick and Heap Sort

6.4 Efficiency of Sorting Algorithms

7. Searching and Hashing
teaching hours: 7 hrs

7.1 Introduction to Searching, Search Algorithms: Sequential Search, Binary Search

7.2 Efficiency of Search Algorithms

7.3 Hashing : Hash Function and Hash Tables, Collision Resolution Techniques

8. Trees and Graphs
teaching hours: 8 hrs

8.1 Concept and Definitions, Basic Operations in Binary Tree, Tree Height, Level and Depth

8.2 Binary Search Tree, Insertion, Deletion, Traversals, Search in BST

8.3 AVL tree and Balancing algorithm, Applications of Trees

8.4 Definition and Representation of Graphs, Graph Traversal, Minimum Spanning Trees:

Kruskal and Prims Algorithm

8.5 Shortest Path Algorithms: Dijksrtra Algorithm

Lab and Practical works

Laboratory Works:

After completing this course, students should have practical knowledge of data structures,

algorithms, and ADTs. The laboratory work includes.

  •  Writing programs with dynamic memory allocation and de-allocation.
  •  Writing programs to implement stack operations.
  •  Writing programs using stack to convert infix expression to postfix/prefix expression and to   evaluate postfix/prefix expression.
  •  Writing programs to implement queue operations for linear, circular, and priority queue.
  •  Writing recursive programs to implement factorial, Fibonacci sequence, GCD, and Towerof   Hanoi algorithms.
  •  Writing programs to implement list using array and linked list.
  •  Writing programs for linked list implementation of stack and queue.
  •  Writing programs to implement sorting, searching and hashing algorithms.
  •  Writing programs to implement Binary Search Trees and AVL Tress.
  •  Writing programs to implement searching, spanning tree and shortest path.