Algorithms and Theory of Computation Handbook, Second Edition  in a two volume set, 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. 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 Networ