Analysis and Design of Algorithms

This unit covers the limitations of algorithm power with respect to lower bound arguments of algorithms. It explains decision trees with examples. It also analyzes P, NP and NP-complete problems.

This unit explains how to cope with some of the limitations of algorithms power. It analyzes the algorithm technique of Backtracking and explains the solution strategy of Branch-and-Bound algorithms. This unit also discusses approximation algorithms for NP-Hard problems like the Traveling Salesman a...

This unit explains the concepts of 'decrease and conquer methodology it uses in various algorithms. It explains the algorithm used for and the insertion sort, Depth-first search, Breadth-first search and topological sorting. It also analyzes the algorithm for generating combinatorial objects.

This unit explains the Divide and Conquer methodology which is a well known general design methodology. It performs different sorting techniques, builds and traverses a binary tree. It also applies the Strassen's matrix method using the Divide and Conquer methodology.

This unit introduces the Dynamic Programming technique with an example to calculate the n Fibonacci number. It explains the dynamic programming approach to compute binomial coefficients. It also describes the Warshall's and Floyd's algorithms.

Unit 11: Dynamic Programming-2 This unit defines the Principle of Optimality and analyzes binary search trees using dynamic programming. It also introduces the Knapsack problem and solves an instance of it using dynamic programming and memory functions.

This unit covers algorithm analysis framework with respect to complexity of an algorithm. It gives an idea about various methods used for analyzing algorithms and explains the techniques involved in amortization. It also includes some case studies in algorithm analysis.

This unit you covers the concepts of Greedy technique algorithms that are Used for optimization problems such as Kruskal's algorithm and F algorithm for finding minimum spanning trees. It also describes the Dijkstra s algorithm for finding single-source shortest paths, and the algorithm for findin...

This unit covers the various definitions of algorithm, its types, properties and the steps for designing it. This unit gives a brief idea on solving a problem using different algorithmic problem solving techniques. It also introduces data structures. their classification and characteristics.

This unit defines recursion and recursive algorithm with examples. It also discusses the empirical analysis of algorithms and algorithm visualization with examples.

This unit explains the types of asymptotic notations. It lists the basic asymptotic efficiency classes. It also describes the efficient analysis of non recursive algorithms with illustrations.

This unit explains the importance of space-time tradeoff in programming. It describes the process of sorting by counting and the input enhancement in string matching. It explains hashing technique the B-Tree technique with respect to space and time tradeoffs.

This unit defines the technique of transform and conquers. It describes the method of presorting, the Gaussian elimination technique and the approach of AVL and 2-3 trees in balanced search trees. It also defines heap sort and the problem reduction strategy.