LECTURE PLAN

Subject : DESIGN AND ANALYSIS OF ALGORITHMS

Code : AD3351
Branch : B.Tech - COMPUTER SCIENCE AND BUSINESS
SYSTEMS
Date:
Semester : III
07/07/2025
Name of the faculty: Ms.R.SARANYA
COURSE OUTCOMES:
After the completion of this course, students will be able to:
CO1: Analyze the efficiency of recursive and non-recursive algorithms mathematically
CO2: Analyze the efficiency of brute force, divide and conquer, decrease and conquer, transform and conquer
algorithmic techniques
CO3: Implement and analyze the problems using dynamic programming and greedy algorithmic techniques.
CO4: Solve the problems using iterative improvement techniques for optimization.
CO5: Compute the limitations of algorithmic power and solve the problems using backtracking and branch and bound
techniques..

PO’s PSO’s
CO’s 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3
1 3 3 3 1 1 - - - 1 1 2 2 3 2 1
2 2 1 1 3 2 - - - 2 2 1 2 2 2 2
3 3 2 1 2 2 - - - 2 1 1 2 1 3 3
4 3 2 3 2 2 - - - 3 3 3 2 2 1 2
5 3 1 2 3 3 - - - 2 2 2 2 3 1 3
AVG 3 2 2 2 2 - - - 2 2 2 2 2 2 2

TEXT BOOKS:
1. Anany Levitin, Introduction to the Design and Analysis of Algorithms, Third Edition, Pearson
Education, 2012.

REFERENCES:
1. Ellis Horowitz, Sartaj Sahni and Sanguthevar Rajasekaran, Computer Algorithms/ C++, Second Edition,
Universities Press, 2019.
2. Thomas H.Cormen, Charles E.Leiserson, Ronald L. Rivest and Clifford Stein, Introduction to Algorithms, Third
Edition, PHI Learning Private Limited, 2012.
3. S. Sridhar, Design and Analysis of Algorithms, Oxford university press, 2014.
4. Alfred V. Aho, John E. Hopcroft and Jeffrey D. Ullman, Data Structures and Algorithms, Pearson
Education,Reprint2006.
 LECTURE PLAN
Subject : DESIGN AND ANALYSIS OF ALGORITHMS
Code : AD3351
Branch : B.Tech - COMPUTER SCIENCE AND BUSINESS
SYSTEMS
Semester : III Date:
Name of the faculty: Ms.R.SARANYA 07/07/2025

SYLLABUS
UNIT I INTRODUCTION 8
Notion of an Algorithm – Fundamentals of Algorithmic Problem Solving – Important Problem Types –
Fundamentals of the Analysis of Algorithm Efficiency – Analysis Framework -Asymptotic Notations and their
properties – Empirical analysis - Mathematical analysis ofRecursive and Non-recursive algorithms – Visualization.
UNIT II BRUTE FORCE AND DIVIDE AND CONQUER 10
Brute Force – String Matching - Exhaustive Search - Traveling Salesman Problem – Knapsack Problem -
Assignment problem. Divide and Conquer Methodology – Multiplication of Large Integers and Strassen’s Matrix
Multiplication – Closest-Pair and Convex - Hull Problems. Decrease and Conquer: - Topological Sorting –
Transform and Conquer: Presorting – Heaps and Heap Sort.
UNIT III DYNAMIC PROGRAMMING AND GREEDY TECHNIQUE 10
Dynamic programming – Principle of optimality - Coin changing problem – Warshall’s and Floyd‘s algorithms –
Optimal Binary Search Trees - Multi stage graph - Knapsack Problem and Memory functions. Greedy Technique –
Dijkstra’s algorithm - Huffman Trees and codes - 0/1 Knapsack problem.
UNIT IV ITERATIVE IMPROVEMENT 8
The Simplex Method-The Maximum-Flow Problem – Maximum Matching in Bipartite Graphs- The Stable marriage
Problem.
UNIT V LIMITATIONS OF ALGORITHM POWER 9
Lower - Bound Arguments - P, NP, NP- Complete and NP Hard Problems. Backtracking – N-Queen problem -
Hamiltonian Circuit Problem – Subset Sum Problem. Branch and Bound – LIFO Search 58 and FIFO search -
Assignment problem – Knapsack Problem – Traveling Salesman Problem - Approximation Algorithms for NP-Hard
Problems – Traveling Salesman problem – Knapsack problem.
TOTAL: 45 PERIODS

Total No. of hours as per syllabus 45

Total No of hours available as per calendar :

Hours (Cumulative) 8 10 10 8 9
Units 1 2 3 4 5

FACULTY IN-CHARGE HOD / CSBS PRINCIPAL

 LECTURE PLAN
Subject : DESIGN AND ANALYSIS OF ALGORITHMS
Code : AD3351
Branch : B.Tech - COMPUTER SCIENCE AND BUSINESS
SYSTEMS
Date:
Semester : III
07/07/2025
Name of the faculty: Ms.R.SARANYA
UNIT I INTRODUCTION 8

Lecture Topics to be Text/ Mode of

Ho Series No. covered Ref teaching
urs
1. Black
1 Notion of an Algorithm T1 Board
2. Fundamentals of Black
2 Algorithmic Problem T1 Board
Solving
3. 3 Black
Important Problem Types T1
Board
4. Fundamentals of the PPT
4
Analysis of Algorithm T1
Efficiency
5. Black
5 Analysis Framework T1 Board
6. Asymptotic Notations and PPT
6 T1
their properties
7. Empirical analysis- Black
7 Mathematical analysis of Board
T1
Recursive and Non-
recursive algorithms
8. Visualization PPT
8 T1

UNIT II BRUTE FORCE AND DIVIDE AND CONQUER 10

Lectur e
Hours Series Topics to be covered Text/Ref Mode of
No. teaching
1. 9. Black
Brute Force T1 Board
2. String Matching - PPT
10. T1
Exhaustive Search
3. Traveling Salesman Black
11. T1 Board
Problem
4. Knapsack Problem- PPT
12. T1
Assignment problem
5. Divide and Conquer Black
13. T1 Board
Methodology
6. Multiplication of Large PPT
14. Integers and Strassen’s T1
Matrix Multiplication
7. 15. Closest-Pair and Convex- T1 PPT
 Hull Problems
8. 16. Black
Decrease and Conquer T1
Board
9. Topological Sorting-– Black
17. T1
Transform and Conquer Board
10. Presorting – Heaps and T1 Black
18.
Heap Sort Board

UNIT III DYNAMIC PROGRAMMING AND GREEDY TECHNIQUE 10

Lecture
Hours Series Topics to be covered Text/Ref Mode of
No. teaching
1. 19. Dynamic programming T1 Black Board
2. Principle of optimality T2 PPT
20.
3. T1 Black Board
21. Coin changing problem
4. Warshall’s and Floyd‘s T1 PPT
22.
algorithms
5. Optimal Binary Search Trees T1 Black Board
23.
6. Multi stage graph T1 PPT
24.
7. 25. Minimal cover T1 PPT
8. 26. Knapsack Problem and T1 Black Board
Memory functions
9. 27. Greedy Technique- Dijkstra’s T1 Black Board
algorithm
10. 28. Huffman Trees and codes - T1 Black Board
0/1 Knapsack problem

UNIT IV ITERATIVE IMPROVEMENT 8

Lectur e
Series
Hours Topics to be covered Text/Ref Mode of
No.
teaching
1. 29. Black
The Simplex Method T2 Board
2. 30. The Simplex Method T2 PPT
3. T2 Black
31. The Maximum-Flow Problem Board
4. 32. The Maximum-Flow Problem T2 PPT

5. 33. Maximum Matching in Bipartite T2 Black

Graphs Board
6. 34. Maximum Matching in Bipartite T2 PPT
Graphs
7. 35. The Stable marriage T2 PPT
Problem.
8. 36. The Stable marriage T2 Black
Problem. Board
UNIT V LIMITATIONS OF ALGORITHM POWER 9
.
Lecture
Hours Series Topics to be covered Text/Ref Mode of
No. teaching
1. 37. Black
Lower - Bound Arguments T2 Board
2. - P, NP, NP- Complete and NP T2 PPT
38.
Hard Problems
3. T2 Black
39. Backtracking– N-Queen problem Board
4. Hamiltonian Circuit Problem T2 PPT
40.
5. Subset Sum Problem. Branch T2 Black
41.
and Bound Board
6. LIFO Search 58 and FIFO search T2 PPT
42.
7. 43. Assignment problem – Knapsack T2 PPT
Problem
8. 44. Traveling Salesman Problem - T2 Black
Approximation Algorithms for Board
NP-Hard Problems
9. Traveling Salesman problem – Black Board /
45. T2
Knapsack problem PPT

TOTAL PERIODS : 45
PROPOSED DATE OF COMPLETION :

FACULTY IN-CHARGE HOD / CS&BS PRINCIPAL

 COURSE DELIVERY PLAN
Subject : DESIGN AND ANALYSIS OF ALGORITHMS
Code : AD3351
Branch : B.Tech - COMPUTER SCIENCE AND BUSINESS
SYSTEMS
Date:
Semester : III
07/07/2025
Name of the faculty: Ms.R.SARANYA

UNIT
HOUR UNIT WISE TOPIC PROPOSED DATE OF
HOUR COMPLETION
1. 1 1 Notion of an Algorithm
2. Fundamentals of Algorithmic Problem
1 2
Solving
3. 1 3 Important Problem Types
4. Fundamentals of the Analysis of Algorithm
1 4
Efficiency
5.
1 5 Analysis Framework
6. Asymptotic Notations and their properties
1 6
7. Empirical analysis- Mathematical analysis
1 7 of Recursive and Non-recursive algorithms
8. Visualization
1 8

9. 2 9 Brute Force
10 2 10 String Matching - Exhaustive Search
11 2 11 Traveling Salesman Problem
12 2 12 Knapsack Problem- Assignment problem
13 2 13 Divide and Conquer Methodology
14 2 14 Multiplication of Large Integers and
Strassen’s Matrix Multiplication
15 2 15 Closest-Pair and Convex- Hull Problems
16 2 16 Decrease and Conquer
17 2 17 Topological Sorting-– Transform and
Conquer
18 2 18 Presorting – Heaps and Heap Sort
19 3 19 Dynamic programming
20 3 20 Principle of optimality
21 3 21 Coin changing problem
22 3 22 Warshall’s and Floyd‘s algorithms
23 3 23 Optimal Binary Search Trees
24 3 24 Multi stage graph
 25 3 25 Minimal cover
26 3 26 Knapsack Problem and Memory functions
27 3 27 Greedy Technique- Dijkstra’s algorithm
28 3 28 Huffman Trees and codes - 0/1 Knapsack
problem

29 4 29 The Simplex Method

30 4 30 The Simplex Method
31 4 31 The Maximum-Flow Problem
32 4 32 The Maximum-Flow Problem
33 4 33 Maximum Matching in Bipartite Graphs
34 4 34 Maximum Matching in Bipartite Graphs
35 4 35 The Stable marriage Problem.

36 4 36 The Stable marriage Problem.

37 5 37 Lower - Bound Arguments

38 5 38 - P, NP, NP- Complete and NP Hard
Problems
39 5 39 Backtracking– N-Queen problem
40 5 40 Hamiltonian Circuit Problem
41 5 41 Subset Sum Problem. Branch and Bound
42 5 42 LIFO Search 58 and FIFO search
43 5 43 Assignment problem – Knapsack Problem
44 5 44 Traveling Salesman Problem -
Approximation Algorithms for NP-Hard
Problems
45 5 45 Traveling Salesman problem – Knapsack
problem

FACULTY IN-CHARGE HOD / CSBS PRINCIPAL

 COURSE DELIVERY PLAN
Subject : DESIGN AND ANALYSIS OF ALGORITHMS
Code : AD3351
Branch : B.Tech - COMPUTER SCIENCE AND BUSINESS
SYSTEMS
Date:
Semester : III
07/07/2025
Name of the faculty: Ms.R.SARANYA

EXP
HOUR EXP NO WISE TOPIC PROPOSED DATE OF
HOUR COMPLETION
Implement recursive and non-recursive
1 1 2 algorithms and study the order of growth
from log2n to n!.
Divide and Conquer - Strassen’s Matrix
2 2 2
Multiplication.
3 3 2 Decrease and Conquer - Topological Sorting
4 3 2 Transform and Conquer - Heap Sort
Dynamic programming - Coin change
5 3 6 Problem, Warshall’s and Floyd‘s algorithms,
Knapsack Problem
Greedy Technique – Dijkstra’s algorithm,
6 4 4
Huffman Trees and codes
7 4 4 Iterative improvement - Simplex Method
Backtracking – N-Queen problem, Subset
8 5 4
Sum Problem
Branch and Bound - Assignment problem,
9 5 4 Traveling Salesman Problem

FACULTY IN-CHARGE HOD / CSBS PRINCIPAL