With an emphasis on data structures and algorithm analysis, this book includes programming examples in C++. The author concentrates on the principles required to select or design a data structure that will most effectively solve a problem.* Provides an understanding of fundamental data structures through clear explanations, illustrations, and case studies. * Uses actual Java code for nearly all algorithms. * Presents basic analysis terminology early in the text and analysis techniques throughout. The techniques provided assume a range of instructional levels so that they may be used by students with varying backgrounds in the subject. * Provides integrated treatment of both in-memory and disk- based algorithm techniques to allow students to see how these techniques are related, and the key differences between them. * Supports the concept that algorithm analysis is practical and helps in the design of real programs by presenting data structure costs and benefits. * Includes exercises as well as many suggestions for projects to provide students with hands-on experience. * Presents several new data structures, including skip lists, multidimensional search trees, and amortized analysis are discussed. * Provides a chapter on the limits of computation: a brief introduction to computability and NP-completeness to permit an easy-to-understand introduction to these topics.
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With an emphasis on data structures and algorithm analysis, this book includes programming examples in C++. The author concentrates on the principles required to select or design a data structure that will most effectively solve a problem.* Provides an understanding of fundamental data structures through clear explanations, illustrations, and case studies. * Uses actual Java code for nearly all algorithms. * Presents basic analysis terminology early in the text and analysis techniques throughout. The techniques provided assume a range of instructional levels so that they may be used by students with varying backgrounds in the subject. * Provides integrated treatment of both in-memory and disk- based algorithm techniques to allow students to see how these techniques are related, and the key differences between them. * Supports the concept that algorithm analysis is practical and helps in the design of real programs by presenting data structure costs and benefits. * Includes exercises as well as many suggestions for projects to provide students with hands-on experience. * Presents several new data structures, including skip lists, multidimensional search trees, and amortized analysis are discussed. * Provides a chapter on the limits of computation: a brief introduction to computability and NP-completeness to permit an easy-to-understand introduction to these topics.
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