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A compendium of fundamental computer science topics and techniques. It illustrates how the topics and techniques come together to deliver efficient solutions to important practical problems. It contains four chapters that cover external memory and parameterized algorithms as well as computational number theory and algorithmic coding theory.

A compendium of fundamental computer science topics, techniques, and applications. It covers self-stabilizing and pricing algorithms as well as the theories of privacy and anonymity, databases, computational games, and communication networks. It also discusses computational topology, natural language processing, and grid computing.

Presenting a complementary perspective to standard books on algorithms, A Guide to Algorithm Design provides a roadmap for readers to determine the difficulty of an algorithmic problem by finding an optimal solution or proving complexity results. It gives a practical treatment of algorithmic complexity and guides readers in solving algorithmic problems. The book offers a comprehensive set of problems with solutions as well as in-depth case studies that demonstrate how to assess the complexity of a new problem.