very nice book
very easy and simple

good reference for students.
simple and elegant work

Fundamentals of algorithmic problem solving, Important problem types, Fundamental data structures.Fundamentals of the Analysis of Algorithm Efficiency : Analysis framework.Asymptotic notations and basic efficiency classes, Mathematical analysis of nonrecursive and recursive algorithms, Example - Fibonacci numbers.Brute Force : Selection sort and bubble sort, Sequential search and brute-force string matching, Exhaustive search.Divide and Conquer : Mergesort, Quicksorst, Binary search. Binary tree traversals and related properties, Multiplication of large integers and Stressen's matrix multiplication.Decrease and Conquer : Insertion sort, Depth first search, Breadth first search, Topological sorting.Algorithms for generating combinatorial objects.Transform and Conquer : Presorting, Balanced search trees, Heaps and heapsort, Problem reduction.Space and Time Tradeoffs : Sorting by counting, Input enhancement in string matching, Hashing.Dynamic Programming : Computing a binomial coefficient, Warshall's and Floyd's algorithms, The Knapsack problem and memory functions.Greedy Technique : Prim's algorithm, Kruskal's algorithm, Dujkstra's algorithm, Huffman trees.Limitations of Algorithm Power : Lower-bound arguments, Decision trees., P, NP and NP-complete problems.Coping with the Limitations of Algorithm Power : Backtracking, Branch-and-bound, Approximation algorithms for NP-hard problems.