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Despite growing interest in the mathematical analysis of algorithms, basic information on methods and models has rarely been directly accessible to practitioners, researchers, or students. This book organizes and presents that knowledge, fully introducing today's primary techniques for mathematically analyzing algorithms.
Robert Sedgewick and the late Philippe Flajolet have drawn from both classical mathematical and computer science material, integrating discrete mathematics, elementary real analysis, combinatorics, algorithms, and data structures. They focus on "average-case" or
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Produktbeschreibung
Despite growing interest in the mathematical analysis of algorithms, basic information on methods and models has rarely been directly accessible to practitioners, researchers, or students. This book organizes and presents that knowledge, fully introducing today's primary techniques for mathematically analyzing algorithms.

Robert Sedgewick and the late Philippe Flajolet have drawn from both classical mathematical and computer science material, integrating discrete mathematics, elementary real analysis, combinatorics, algorithms, and data structures. They focus on "average-case" or "probabilistic" analysis, while also covering tools for "worst case" or "complexity" analysis. Improvements in this edition include:

* Upgraded figures and code

* Newer style for presenting much of the text's math

* An all-new chapter on trees

This book's thorough, self-contained coverage will help readers appreciate the field's challenges, prepare them for advanced results covered in Donald Knuth's books, and provide the background they need to keep abreast of new research. Coverage includes: recurrences, generating functions, asymptotics, trees, strings, maps, sorting, tree search, string search, and hashing algorithms. Ideal for junior- or senior-level courses on mathematical analysis of algorithms, this book will also be useful in courses on discrete mathematics for computer scientists, and in introducing mathematics students to computer science principles related to algorithms and data structures.

Product Description
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
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. Authors Robert Sedgewick and the late Philippe Flajolet 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. Improvements and additions in this new edition include upgraded figures and code, an all-new chapter introducing analytic combinatorics, and simplified derivations via analytic combinatorics throughout. The book's thorough, self-contained coverage will help readers appreciate the field's challenges and prepare them for advanced study.
Autorenporträt
Robert Sedgewick, der an der Stanford University bei Donald Knuth promoviert hat, ist Professor für Informatik an der Princeton University. Als Berater für Java war der renommierte Software-Consultant Michael Schidlowski an der Entstehung des Buches beteiligt.