B.Sc. (Computer Science) Design and Analysis of Algorithms Syllabus - Mumbai University
This is the FY BSc Computer Science syllabus under NEP 2020, in force from the academic year 2024-25. The University still sets the earlier Choice Based papers alongside it — her Summer 2026 third-year timetables name that scheme — so check which scheme your exam form names before you revise.
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Syllabus for Design and Analysis of Algorithms
The University sets the practical for this subject separately, in Computer Science Practical 2, as Module 1. It carries its own credits, so it is examined as a paper of its own.
Module I
- Introduction to algorithms - What is algorithm, analysis of algorithm, Types of complexity, Running time analysis, How to Compare Algorithms, Rate of Growth, Types of Analysis, Asymptotic Notation, Big-O Notation, Omega-Ω Notation, Theta-Θ Notation, Asymptotic Analysis, Performance characteristics of algorithms, Estimating running time / number of steps of executions on paper, Idea of Computability
- Introduction to Data Structures - What is data structure, types, Introduction to Array(1-d & 2-d), Stack and List data structures, operations on these data structures, advantages disadvantages and applications of these data structures like solving linear equations, Polynomial Representation, Infix-to-Postfix conversion.
- Recursion - What is recursion, Recursion vs Iteration, recursion applications like Factorial of a number, Fibonacci series & their comparative analysis with respect to iterative version, Tower of Hanoi problem.
- Basic Sorting Techniques - Bubble, Selection and Insertion Sort & their comparative analysis
Module II
- Searching Techniques - Linear Search and its types, Binary Search and their comparative analysis, Selection Techniques - Selection by Sorting, Partition-based Selection Algorithm, Finding the Kth Smallest Elements in Sorted Order & their comparative analysis, String Algorithms - Pattern matching in strings, Brute Force Method & their comparative analysis
- Algorithm Design Techniques - Introduction to various types of classifications/design criteria and design techniques, Greedy Technique - Concept, Advantages & Disadvantages, Applications, Implementation using problems like - file merging problem. Divide-n-Conquer - Concept, Advantages & Disadvantages, Applications, Implementation using problems like - merge sort, Strassen's Matrix Multiplication
- Dynamic Programming - Concept, Advantages & Disadvantages, Applications, Implementation using problems like - Fibonacci series, Factorial of a number, Longest Common subsequence
- Backtracking Programming - Concept, Advantages & Disadvantages, Applications, Implementation using problems like N-Queen Problem
Text Books
- 1 Data Structure and Algorithm Using Python, Rance D. Necaise, Wiley India Edition, 2016.
- 2 Data Structures and Algorithms Made Easy, Narasimha Karumanchi, CareerMonk Publications, 2016.
- 3 Introduction to Algorithms, Thomas H. Cormen, 3rd Edition, PHI.
- 1 Introduction to the Design and Analysis of Algorithms, Anany Levitin, Pearson, 3rd Edition, 2011.
- 2 Design and Analysis of Algorithms, S. Sridhar, Oxford University Press, 2014.
Reproduced from the University of Mumbai syllabus for B.Sc. (Computer Science) under NEP 2020, in force from the academic year 2024-25. Wording is as printed in that syllabus. Module numbering is as printed there too.