Analysis and Design of Algorithms

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ANALYSIS AND DESIGN 3150703
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Code: 3150703 Credits: 5 Semester 5 Common

Analysis and Design of Algorithms

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Analysis and Design of Algorithms Syllabus — Unit-wise Content

The official GTU curriculum for Analysis and Design of Algorithms (subject code 3150703) as prescribed for Common · Semester 5 divides the course into 9 units, covering 65 listed topics. The unit-wise breakdown below is read from the GTU syllabus document for this subject code, so you can check what the course actually covers before deciding which papers to attempt.

Download the official syllabus PDF (3150703)

Unit 1 Basics of Algorithms and Mathematics

2 lecture hours

  • What is an algorithm?
  • Mathematics for Algorithmic Sets
  • Functions and Relations
  • Vectors and Matrices
  • Linear Inequalities and Linear Equations

Unit 2 Analysis of Algorithm

8 lecture hours

  • The efficient algorithm
  • Best and worst case analysis
  • Amortized analysis
  • Asymptotic Notations
  • Analyzing control statement
  • Loop invariant and the correctness of the algorithm
  • Sorting Algorithms and analysis: Bubble sort
  • Selection sort
  • Insertion sort
  • Shell sort Heap sort
  • Sorting in linear time : Bucket sort
  • Radix sort and Counting sort

Unit 3 Divide and Conquer Algorithm

6 lecture hours

  • Recurrence and different methods to solve recurrence
  • Multiplying large Integers Problem
  • Problem Solving using divide and conquer algorithm - Binary Search
  • Max-Min problem
  • Sorting (Merge Sort
  • Quick Sort)
  • Matrix Multiplication

Unit 4 Dynamic Programming

5 lecture hours

  • The Principle of Optimality
  • Problem Solving using Dynamic Programming – Calculating the Binomial Coefficient
  • Making Change Problem
  • Assembly Line-Scheduling
  • Knapsack problem
  • All Points Shortest path
  • Matrix chain multiplication
  • Longest Common Subsequence

Unit 5 Greedy Algorithm

5 lecture hours

  • General Characteristics of greedy algorithms
  • Problem solving using Greedy Algorithm - Activity selection problem
  • Elements of Greedy Strategy
  • Minimum Spanning trees (Kruskal’s algorithm
  • Prim’s algorithm)
  • Graphs: Shortest paths
  • The Knapsack Problem
  • Job Scheduling Problem
  • Huffman code

Unit 6 Exploring Graphs

10 lecture hours

  • 04 Subject Code: 3150703 An introduction using graphs and games
  • Undirected Graph
  • Directed Graph
  • Traversing Graphs
  • Depth First Search
  • Breath First Search
  • Topological sort
  • Connected components

Unit 7 Backtracking and Branch and Bound

3 lecture hours

  • The Eight queens problem
  • Knapsack problem
  • Travelling Salesman problem
  • Minimax principle

Unit 8 String Matching

3 lecture hours

  • The naive string matching algorithm
  • The Rabin-Karp algorithm
  • String Matching with finite automata
  • The Knuth-Morris-Pratt algorithm

Unit 9 Introduction to NP-Completeness

5 lecture hours

  • The class P and NP, Polynomial reduction
  • NP- Completeness Problem
  • NP-Hard Problems
  • Travelling Salesman problem
  • Hamiltonian problem
  • Approximation algorithms
  • Randomized algorithms
  • Class of problems beyond NP – P SPACE

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