An Introduction to the Analysis of Algorithms

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Robert Sedgewick
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具体描述

Despite growing interest, basic information on methods and models for mathematically analyzing algorithms has rarely been directly accessible to practitioners, researchers, or students. An Introduction to the Analysis of Algorithms, Second Edition, organizes and presents that knowledge, fully introducing primary techniques and results in the field. Robert Sedgewick and the late Philippe Flajolet have drawn from both classical mathematics and computer science, integrating discrete mathematics, elementary real analysis, combinatorics, algorithms, and data structures. They emphasize the mathematics needed to support scientific studies that can serve as the basis for predicting algorithm performance and for comparing different algorithms on the basis of performance. Techniques covered in the first half of the book include recurrences, generating functions, asymptotics, and analytic combinatorics. Structures studied in the second half of the book include permutations, trees, strings, tries, and mappings. Numerous examples are included throughout to illustrate applications to the analysis of algorithms that are playing a critical role in the evolution of our modern computational infrastructure. Improvements and additions in this new edition include * Upgraded figures and code * An all-new chapter introducing analytic combinatorics * Simplified derivations via analytic combinatorics throughout The book's thorough, self-contained coverage will help readers appreciate the field's challenges, prepare them for advanced results-covered in their monograph Analytic Combinatorics and in Donald Knuth's The Art of Computer Programming books-and provide the background they need to keep abreast of new research. "[Sedgewick and Flajolet] are not only worldwide leaders of the field, they also are masters of exposition. I am sure that every serious computer scientist will find this book rewarding in many ways." -From the Foreword by Donald E. Knuth

用户评价

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曾经的教材,我考得还可以;每当我捣鼓欧拉工程的题目(https://github.com/greatabel/puzzle_I_cracked/tree/master/3ProjectEuler),涉及到实现个特定结构或者排列组合时间空间复杂度时候,就顺便对应复习章节,毕竟现实生活中30%的编程+70%管理,编程主要也是架构和保密的算法小模块,再就是审核代码,工作量不足啊,看看英文原版复习下算法和英语

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曾经的教材,我考得还可以;每当我捣鼓欧拉工程的题目(https://github.com/greatabel/puzzle_I_cracked/tree/master/3ProjectEuler),涉及到实现个特定结构或者排列组合时间空间复杂度时候,就顺便对应复习章节,毕竟现实生活中30%的编程+70%管理,编程主要也是架构和保密的算法小模块,再就是审核代码,工作量不足啊,看看英文原版复习下算法和英语

评分

评分

曾经的教材,我考得还可以;每当我捣鼓欧拉工程的题目(https://github.com/greatabel/puzzle_I_cracked/tree/master/3ProjectEuler),涉及到实现个特定结构或者排列组合时间空间复杂度时候,就顺便对应复习章节,毕竟现实生活中30%的编程+70%管理,编程主要也是架构和保密的算法小模块,再就是审核代码,工作量不足啊,看看英文原版复习下算法和英语

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##5星改成了4星……

评分

评分

曾经的教材,我考得还可以;每当我捣鼓欧拉工程的题目(https://github.com/greatabel/puzzle_I_cracked/tree/master/3ProjectEuler),涉及到实现个特定结构或者排列组合时间空间复杂度时候,就顺便对应复习章节,毕竟现实生活中30%的编程+70%管理,编程主要也是架构和保密的算法小模块,再就是审核代码,工作量不足啊,看看英文原版复习下算法和英语

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##个人认为讲的太理论了一点

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