S.NO.
|
Topics to be Covered
|
No. of Lectures
|
First Term
|
1.
|
Introduction to algorithms, algorithm design, analysis, validation.
|
1
|
2.
|
Review of growth of function with numerical problems
|
2
|
3.
|
Recurrence: substitution method, iteration method
|
2
|
4.
|
Recurrence: Recursion tree method
|
1
|
5.
|
Recurrence : Master’s method with proof
|
2
|
6.
|
Incremental Approach: Insertion Sort
|
1
|
7.
|
Divide and conquer approach:
Merge Sort
Quick Sort
|
2
|
8.
|
Median and order Statistics
|
2
|
9.
|
Data structure for Disjoint sets
|
2
|
10.
|
Strassen’s algorithms for matrix multiplications
|
1
|
11.
|
Dynamic programming:
Elements of Dynamic programming
|
1
|
Matrix Chain multiplication
|
2
|
Longest Common Subsequence
|
1
|
Optimal Binary Search Tree
|
2
|
Second Term
|
12.
|
Greedy algorithms:
Elements of Greedy Strategy
|
1
|
Activity Selection problem
|
1
|
Knapsack Problem
|
1
|
Huffman Coding
|
1
|
Task Scheduling Problem
|
1
|
13.
|
Graph Algorithms:
Representation of graphs
|
1
|
Breadth First Search
|
1
|
Depth First Search
|
1
|
Topological sort & connected Components
|
1
|
14.
|
Spanning Tree Problem:
Kruskal’s Algorithm
Prim’s Algorithm
|
2
|
15.
|
Shortest Path problem:
Dijkstra’s Algorithm
Bellman Ford Algorithm
|
2
|
16.
|
All Pair Shortest path problem:
Floyd Warshall algorithm
|
2
|
17.
|
String Matching Problems:
Naïve String Matching algorithms
|
1
|
Rabin Karp string Matching
|
1
|
String Matching With Finite Automata
|
1
|
Knuth-Morris Pratt Algorithm
|
1
|
Third Term
|
18.
|
NP-Complete Problem:
|
|
Polynomial time Verification
|
1
|
NP-Completeness & reducibility
|
1
|
NP-Completeness Proof
|
2
|
NP-Completeness Problems
|
2
|
1. T. H. Cormen, C. E. Leiserson, R. L. Rivest, Clifford Stein, “Introduction to Algorithms”, 2nd Ed., PHI, 2004.