VTU 2022 Scheme  ·  Degree  ·  CSE

Introduction to Algorithms BCS755B

Module-wise notes, PYQs, and a built-in resource explorer — everything you need to crack BCS755B in one focused page.

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CodeBCS755B
Credits03
CIE / SEE50 / 50
TypeTheory
Exam3 Hours
Hours / Week3:0:0:0
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Last Updated:  15 March 2026

Module Overview

M1

Module 1 Overview

INTRODUCTION: What is an Algorithm?, Fundamentals of Algorithmic Problem Solving, Important problem Types, Fundamental Data Structures, Analysis Framework, Asymptotic Notations and Basic Efficiency Classes, ,Analysis Framework, Asymptotic Notations and Basic Efficiency Classes,

Chapter 1 (Sections 1.1 to 1.4), Chapter 2 (2.1, 2.2)

M2

Module 2 Overview

FUNDAMENTALS OF THE ANALYSIS OF ALGORITHM EFFICIENCY: Mathematical Analysis of Non-recursive Algorithms, Mathematical Analysis of Recursive Algorithms.

BRUTE FORCE APPROACHES: Selection Sort and Bubble Sort, Sequential Search and Brute Force String Matching.

Chapter 2(Sections 2.3,2.4), Chapter 3(Section 3.1,3.2)

M3

Module 3 Overview

Exhaustive Search (Travelling Salesman problem and Knapsack Problem).

Depth First search and Breadth First search.

DECREASE-AND-CONQUER: Insertion Sort, Topological Sorting.

DIVIDE AND CONQUER: Merge Sort, Binary Tree Traversals.

Chapter 3(3.4,3.5), Chapter 4 (Sections 4.1,4.2), Chapter 5 (Section 5.1,5.3)

M4

Module 4 Overview

TRANSFORM-AND-CONQUER: Balanced Search Trees (AVL Trees), Heaps and Heapsort.

SPACE-TIME TRADEOFFS: Sorting by Counting: Comparison counting sort, Input Enhancement in String Matching: Horspool's Algorithm, Hashing.

Chapter 6 (Sections 6.3,6.4), Chapter 7 (Sections 7.1,7.2, 7.3)

M5

Module 5 Overview

DYNAMIC PROGRAMMING: Three basic examples, The Knapsack Problem and Memory Functions.

THE GREEDY METHOD: Kruskal's Algorithm, Dijkstra's Algorithm, Huffman Trees and Codes.

Chapter 8 (Sections 8.1,8.2), Chapter 9 (Sections 9.2,9.3,9.4)

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Frequently Asked Questions

What is BCS755B (Introduction to Algorithms BCS755B)?

Introduction to Algorithms BCS755B is a VTU course covered through module-wise syllabus, notes, and PYQ-driven exam practice available on this page.

How many credits is BCS755B?

Credits for BCS755B: 03.

Are notes and previous year question papers available for BCS755B?

Yes. You can access organized notes, PDFs, and PYQ material from the file explorer/resources section on this page.

How should I prepare Introduction to Algorithms BCS755B for VTU exams?

Start with module summaries, solve recent PYQs unit-wise, and finish with complete paper practice under time constraints for SEE readiness.

Is this BCS755B page updated for current VTU scheme?

Yes, this page is maintained with current scheme-oriented materials and practical exam-focused resource curation.

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About Introduction to Algorithms (BCS755B)

Introduction to Algorithms (BCS755B) is a critical course in the VTU curriculum, essential for any student looking to master the foundations of engineering. It covers key theoretical frameworks and practical concepts that are widely used in the industry today, ensuring students are well-prepared for both exams and their future careers.

Success Strategy

Focus on numerical proofs and architectural flowcharts. Practicing the math-heavy derivations is key for scoring the full 20 marks in these modules.

📘 Detailed Syllabus & Topic Breakdown

Detailed Subject Overview

Introduction to Algorithms (BCS755B) is designed to provide a comprehensive look into the core methodologies and advanced theories that define this field. Understanding this subject is fundamental for anyone looking to excel in modern technical domains and industrial engineering.

By studying this course, you will learn how to approach complex problems with a structured mindset, optimizing systems for better performance and reliability—skills that are highly valued in both AI research and software architecture.

Module-by-Module Breakdown

Module 1
Essential

Master the INTRODUCTION What is an Algorithm?, Fundamentals of Algorithmic Problem Solving, Important problem Types, Fundamental Data Structures, Analysis Framework, Asymptot...

Key: Exam Priority Concept
Module 2
Math Heavy

Master the FUNDAMENTALS OF THE ANALYSIS OF ALGORITHM EFFICIENCY Mathematical Analysis of Non-recursive Algorithms, Mathematical Analysis of Recursive Algorithms....

Key: Exam Priority Concept
Module 3
Logic Core

Master the DECREASE-AND-CONQUER Insertion Sort, Topological Sorting....

Key: Exam Priority Concept
Module 4
Exam Focus

Master the TRANSFORM-AND-CONQUER Balanced Search Trees (AVL Trees), Heaps and Heapsort....

Key: Exam Priority Concept
Module 5
High Weight

Master the DYNAMIC PROGRAMMING Three basic examples, The Knapsack Problem and Memory Functions....

Key: Exam Priority Concept

Professional Career Relevance

ADA is critical for Competitive Programming and designing efficient systems in HFT (High Frequency Trading) and AI optimization. Mastering these concepts prepares you for high-demand roles in Data Science, System Architecture, and Technical Leadership in top-tier tech companies.

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