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An Introduction To Data Structures And Algorithms,Used
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Data structures and algorithms are presented at the college level in a highly accessible format that presents material with onepage 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 selfexplanatory 'pseudocode.' * Chapters 14 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 513 progress at a faster pace. The material is suitable for undergraduates or firstyear graduates who need only review Chapters 1 4. * This book may be used for a onesemester introductory course (based on Chapters 14 and portions of the chapters on algorithm design, hashing, and graph algorithms) and for a onesemester advanced course that starts at Chapter 5. A yearlong 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 comparisonbased structures. * Chapter 13 on parallel models of computation is something of a minibook itself, and a good way to end a course. Although it is not clear what parallel
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