2nd Edition

Algorithms and Theory of Computation Handbook - 2 Volume Set

    1938 Pages 400 B/W Illustrations
    by Chapman & Hall

    Algorithms and Theory of Computation Handbook, Second Edition 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.

    New to the Second Edition
    Along with updating and revising many of the existing chapters, this second edition contains more than 20 new chapters. This edition now covers external memory, parameterized, self-stabilizing, and pricing algorithms as well as the theories of algorithmic coding, privacy and anonymity, databases, computational games, and communication networks. It also discusses computational topology, computational number theory, natural language processing, and grid computing and explores applications in intensity-modulated radiation therapy, voting, DNA research, systems biology, and financial derivatives.

    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.

    General Concepts and Techniques

    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

    Special Topics and Techniques

    Computational Geometry I

    Computational Geometry II

    NEW! Computational Topology

    Robot Algorithms

    Vision and Image Processing Algorithms

    Graph Drawing Algorithms

    NEW! Algorithmics in Intensity-Modulated Radiation Therapy

    VLSI Layout Algorithms

    Cryptographic Foundations

    Encryption Schemes


    Crypto Topics and Applications I

    Crypto Topics and Applications II

    NEW! Secure Multiparty Computation

    NEW! Voting Schemes

    NEW! Auction Protocols

    Pseudorandom Sequences and Stream Ciphers

    NEW! Theory of Privacy and Anonymity

    NEW! Database Theory: Query Languages

    Scheduling Algorithms

    NEW! Computational Game Theory: An Introduction

    Artificial Intelligence Search Algorithms

    NEW! Algorithmic Aspects of Natural Language Processing

    Algorithmic Techniques for Regular Networks of Processors

    Parallel Algorithms

    NEW! Self-Stabilizing Algorithms

    NEW! Theory of Communication Networks

    NEW! Network Algorithmics

    NEW! Algorithmic Issues in Grid Computing

    NEW! Uncheatable Grid Computing

    NEW! DNA Computing: A Research Snapshot

    NEW! Computational Systems Biology

    NEW! Pricing Algorithms for Financial Derivatives



    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.

    … a compilation that will appeal to professionals and students alike; together with those engaged in research and especially those contemplating embarking upon research. … This second edition contains twenty-one new chapters and a thorough updating and revision of many of the chapters from the first edition. A consistent style has been adopted … the sections detailing research issues and sources for further information will ensure that this edition remains an excellent reference source for years to come. I recommend this text as both a teaching aid and a reference source whose utility can only but increase in the coming years.
    International Statistical Review (2011), 79, 1

    The detailed treatment of algorithmic foundations for various subfields of computer science makes the handbook relevant for abroad community of researchers in computer science, operations research, and optimization ... the handbook is a useful reference and presents a broad outlook on the vast field of algorithms and the theory of computation.
    Computing Reviews, May 2010

    Praise for the First Edition
    … excellent survey of the state of the art … highly recommended for anyone interested in algorithms, data structures and the theory of computation … indispensable book of reference for all computer scientists, researchers and professional programmers.
    —R. Kemp, Zentralblatt MATH, Vol. 926