Algorithms and Theory of Computation Handbook, Volume 1 : General Concepts and Techniques book cover
2nd Edition

Algorithms and Theory of Computation Handbook, Volume 1
General Concepts and Techniques

ISBN 9781138113930
Published May 31, 2017 by Chapman and Hall/CRC
988 Pages 227 B/W Illustrations

FREE Standard Shipping
USD $89.95

Prices & shipping based on shipping country


Book Description

Algorithms and Theory of Computation Handbook, Second Edition: General Concepts and Techniques provides an up-to-date compendium of fundamental computer science topics and techniques. It also illustrates how the topics and techniques come together to deliver efficient solutions to important practical problems. Along with updating and revising many of the existing chapters, this second edition contains four new chapters that cover external memory and parameterized algorithms as well as computational number theory and algorithmic coding theory.

This best-selling handbook continues to help computer professionals and engineers find significant information on various algorithmic topics. The expert contributors clearly define the terminology, present basic results and techniques, and offer a number of current references to the in-depth literature. They also provide a glimpse of the major research issues concerning the relevant topics.

Table of Contents

Algorithms Design and Analysis Techniques


Sorting and Order Statistics

Basic Data Structures

Topics in Data Structures

Multidimensional Data Structures for Spatial Applications

Basic Graph Algorithms

Advanced Combinatorial Algorithms

Dynamic Graph Algorithms

NEW! External Memory Algorithms and Data Structures

Average Case Analysis of Algorithms

Randomized Algorithms

Pattern Matching in Strings

Text Data Compression Algorithms

General Pattern Matching

NEW! Computational Number Theory

Algebraic and Numerical Algorithms

Applications of FFT and Structured Matrices

Basic Notions in Computational Complexity

Formal Grammars and Languages


Complexity Classes

Reducibility and Completeness

Other Complexity Classes and Measures

NEW! Parameterized Algorithms

Computational Learning Theory

NEW! Algorithmic Coding Theory

Parallel Computation: Models and Complexity Issues

Distributed Computing: A Glimmer of a Theory

Linear Programming

Integer Programming

Convex Optimization

Simulated Annealing Techniques

Approximation Algorithms for NP-Hard Optimization Problems

View More



Mikhail J. Atallah is a distinguished professor of computer science at Purdue University.

Marina Blanton is an assistant professor in the computer science and engineering department at the University of Notre Dame