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Synopsis
Data structures and algorithms are presented at the college level in a highly accessible format that presents material with one-page displays in a way that will appeal to both teachers and students. The thirteen chapters cover: Models of Computation, Lists, Induction and Recursion, Trees, Algorithm Design, Hashing, Heaps, Balanced Trees, Sets Over a Small Universe, Graphs, Strings, Discrete Fourier Transform, Parallel Computation. Key features: Complicated concepts are expressed clearly in a single page with minimal notation and without the "clutter" of the syntax of a particular programming language; algorithms are presented with self-explanatory "pseudo-code." * Chapters 1-4 focus on elementary concepts, the exposition unfolding at a slower pace. Sample exercises with solutions are provided. Sections that may be skipped for an introductory course are starred. Requires only some basic mathematics background and some computer programming experience. * Chapters 5-13 progress at a faster pace. The material is suitable for undergraduates or first-year graduates who need only review Chapters 1 -4. * This book may be used for a one-semester introductory course (based on Chapters 1-4 and portions of the chapters on algorithm design, hashing, and graph algorithms) and for a one-semester advanced course that starts at Chapter 5. A year-long course may be based on the entire book. * Sorting, often perceived as rather technical, is not treated as a separate chapter, but is used in many examples (including bubble sort, merge sort, tree sort, heap sort, quick sort, and several parallel algorithms). Also, lower bounds on sorting by comparisons are included with the presentation of heaps in the context of lower bounds for comparison-based structures. * Chapter 13 on parallel models of computation is something of a mini-book itself, and a good way to end a course. Although it is not clear what parallel
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About the Author
James A. Storer received his B.A. in Mathematics and Computer Science from Cornell University, his M.A. in Computer Science from Princeton University, and his Ph.D. in Computer Science from Princeton University. After leaving Princeton he was a researcher at Bell Laboratories in Murray Hill, New Jersey. He then came to Brandeis University, where he is currently Chair of the Computer Science Department and member of the Brandeis Center for Complex Systems.
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An Introduction to Data Structures and Algorithms
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Hardback. Condition: Good. Data structures and algorithms are presented at the college level in a way that is unique in content and presentation from current available texts. A highly accessible format presents algorithms with one page displays that will appeal to both students and teachers of computer science. The thirteen chapters systematically and comprehensively cover Models of Computation, Lists, Induction and Recursion, Trees, Algorithm Design, Hashing, Heaps, Balanced Trees, Sets Over a Small Universe, Discrete Fourier Transform, Strings, Graphs, Parallel Computation. Seller Inventory # CIN0817642536G
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An Introduction to Data Structures and Algorithms
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Hardback. Condition: Good. Data structures and algorithms are presented at the college level in a way that is unique in content and presentation from current available texts. A highly accessible format presents algorithms with one page displays that will appeal to both students and teachers of computer science. The thirteen chapters systematically and comprehensively cover Models of Computation, Lists, Induction and Recursion, Trees, Algorithm Design, Hashing, Heaps, Balanced Trees, Sets Over a Small Universe, Discrete Fourier Transform, Strings, Graphs, Parallel Computation. Seller Inventory # CIN0817642536G
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An Introduction to Data Structures and Algorithms
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