Algorithms and Theory of Computation Handbook - 2 Volume Set

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

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.

General Concepts and Techniques: Algorithms Design and Analysis Techniques. Searching. 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. On-Line Algorithms. External Memory Algorithms and Data Structures. Average Case Analysis of Algorithms. Randomized Algorithms. Pattern Matching in Strings. Text Data Compression Algorithms. General Pattern Matching. Computational Number Theory. Algebraic and Numerical Algorithms. Applications of FFT and Structured Matrices. Basic Notions in Computational Complexity. Formal Grammars and Languages. Computability. Complexity Classes. Reducibility and Completeness. Other Complexity Classes and Measures. Parameterized Algorithms. Computational Learning Theory. Algorithmic Coding Theory. Parallel Computation. Distributed Computing. 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. Computational Topology. Robot Algorithms. Vision and Image Processing Algorithms. Graph Drawing Algorithms. Algorithmics in Intensity-Modulated Radiation Therapy. VLSI Layout Algorithms. Cryptographic Foundations. Encryption Schemes. Cryptanalysis. Crypto Topics and Applications I. Crypto Topics and Applications II. Secure Multi-Party Computation. Electronic Cash. Voting Schemes. Auction Protocols. Pseudorandom Sequences and Stream Ciphers. Theory of Privacy and Anonymity. Database Theory. Scheduling Algorithms. Computational Game Theory. Artificial Intelligence Search Algorithms. Algorithmic Aspects of Natural Language Processing. Algorithmic Techniques for Regular Networks of Processors. Parallel Algorithms. Self-Stabilizing Algorithms. Theory of Communication Networks. Network Algorithmics. Algorithmic Issues in Grid Computing. Uncheatable Grid Computing. DNA Computing. Computational Systems Biology. Pricing Algorithms for Financial Derivatives.