Mode of access: World Wide Web.

System requirements: Adobe Acrobat Reader.

Title from web page (viewed May 31, 2019).

Includes bibliographical references and index.

Algorithms -- Growth of functions -- Backtracking -- Divide and conquer -- Greedy algorithms -- Dynamic programming -- Elementary graph algorithms -- Minimal spanning tree -- Single-source shortest paths -- All pairs shortest paths -- Flow networks -- Polynomial multiplication, FFT and DFT -- String matching -- Sorting networks -- NP-Complete problems.

"In computer science, an algorithm is an unambiguous specification of how to solve a class of problems. Algorithms can perform calculation, data processing and automated reasoning tasks. As an effective method, an algorithm can be expressed within a finite amount of space and time and in a well-defined formal language for calculating a function. Starting from an initial state and initial input (perhaps empty), the instructions describe a computation that, when executed, proceeds through a finite number of well-defined successive states, eventually producing "output" and terminating at a final ending state. The transition from one state to the next is not necessarily deterministic; some algorithms, known as randomized algorithms, incorporate random input. This book introduces a set of concepts in solving problems computationally such as Growth of Functions; Backtracking; Divide and Conquer; Greedy Algorithms; Dynamic Programming; Elementary Graph Algorithms; Minimal Spanning Tree; Single Source Shortest Paths; All Pairs Shortest Paths; Flow Networks; Polynomial Multiplication, to ways of solving NP-Complete Problems, supported with comprehensive, and detailed problems and solutions, making it an ideal resource to those studying computer science, computer engineering and information technology."-- Publisher's website.