Algorithm Design and Applications

Goodrich, Michael T. / Tamassia, Roberto

1. Auflage Dezember 2014
800 Seiten, Hardcover
Wiley & Sons Ltd

ISBN: 978-1-118-33591-8

John Wiley & Sons

Weitere Versionen

Introducing a NEW addition to our growing library of computer science titles, Algorithm Design and Applications, by Michael T. Goodrich & Roberto Tamassia! Algorithms is a course required for all computer science majors, with a strong focus on theoretical topics. Students enter the course after gaining hands-on experience with computers, and are expected to learn how algorithms can be applied to a variety of contexts. This new book integrates application with theory.

Goodrich & Tamassia believe that the best way to teach algorithmic topics is to present them in a context that is motivated from applications to uses in society, computer games, computing industry, science, engineering, and the internet. The text teaches students about designing and using algorithms, illustrating connections between topics being taught and their potential applications, increasing engagement.

Preface

* Algorithm Analysis

Part I: Data Structures

* Basic Data Structures

* Binary Search Trees

* Balanced Binary Search Trees

* Priority Queues and Heaps

* Hash Tables

* Union-Find Structures

Part II: Sorting and Selection

* Merge-Sort and Quick-Sort

* Fast Sorting and Selection

Part III: Fundamental Techniques

* The Greedy Method

* Divide-and Conquer

* Dynamic Programming

Part IV: Graph Algorithms

* Graphs and Traversals

* Shortest Paths

* Minimum Spanning Trees

* Network Flow and Matching

Part V: Computational Intractability

* NP-Completeness

* Approximation Algorithms

Part VI: Additional Topics

* Randomized Algorithms

* B-Trees and External-Memory

* Multi-Dimensional Searching

* Computational Geometry

* String Algorithms

* Cryptography

* The Fast Fourier Transform

* Linear Programming

A. Useful
Mathematical Facts

Bibliography

Index

Michael T. Goodrich received his B.A. in Mathematics and Computer Science from Calvin College in 1983 and his PhD in Computer Sciences from Purdue University in 1987. Dr. Goodrich's research is directed at the design of high performance algorithms and data structures for solving large-scale problems motivated from information assurance and security, the Internet, Bioinformatics, and geometric computing. He has pioneered and led research on efficient solutions to a number of fundamental problems, including sorting, convex hull construction, linear programming, privacy-preserving data access, network traceback, and data authentication.

M. T. Goodrich, Johns Hopkins University; R. Tamassia, Brown University