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Introduction: What is an Algorithm? , Algorithm Specification, Analysis Framework, Performance Analysis: Space complexity, Time complexity, Asymptotic Notations: Big-oh notation(O),Omega notation(Ω),Theta notation(ϴ), and Little-oh notation(o), Mathematical analysis of Non-Recursive and recursive Algorithm with Examples. Important Problem Types: Sorting, Searching, String processing, ......

Divide and Conquer: General method, Binary search, Recurrence equation for divide and conquer, Finding the maximum and minimum, Merge sort, Quick sort , Strassen’s matrix multiplication, Advantages and Disadvantages of divide and conquer. Decrease and Conquer Approach: Topological Sort.

Greedy Method: General method, Coin Change Problem, Knapsack Problem, Job sequencing with deadlines. Minimum cost spanning trees: Prim’s Algorithm, Kruskal’s Algorithm. Single source shortest paths: Dijkstra’s Algorithm. Optimal Tree problem: Huffman Trees and Codes.Transform and Conquer Approach: Heaps and Heap Sort.

Dynamic Programming: General method with examples, Multistage Graphs, Transitive Closure: Warshall’s Algorithm, All Pairs Shortest paths: Floyd’s Algorithm, Optimal Binary Search Trees, Knapsack problem, Bellman-Ford Algorithm, Travelling Sales Person problem, Reliability design.

Dynamic Programming