"This is a wonderful book, covering both classical and contemporary topics in algorithms. I look forward to trying it out in my algorithms class. I especially like the diversity in topics and difficulty of the problems." ROBERT TARJAN, PRINCETON UNIVERSITY "The clarity of explanation is excellent. I like the inclusion of the three types of exercises very much." MING-YANG KAO, NORTHWESTERN UNIVERSITY "Goodrich and Tamassia have designed a book that is both remarkably comprehensive in its coverage and innovative in its approach. Their emphasis on motivation and applications, throughout the text…mehr
"This is a wonderful book, covering both classical and contemporary topics in algorithms. I look forward to trying it out in my algorithms class. I especially like the diversity in topics and difficulty of the problems." ROBERT TARJAN, PRINCETON UNIVERSITY "The clarity of explanation is excellent. I like the inclusion of the three types of exercises very much." MING-YANG KAO, NORTHWESTERN UNIVERSITY "Goodrich and Tamassia have designed a book that is both remarkably comprehensive in its coverage and innovative in its approach. Their emphasis on motivation and applications, throughout the text as well as in the many exercises, provides a book well-designed for the boom in students from all areas of study who want to learn about computing. The book contains more than one could hope to cover in a semester course, giving instructors a great deal of flexibility and students a reference that they will turn to well after their class is over." MICHAEL MITZENMACHER, HARVARD UNIVERSITY "I highly recommend this accessible roadmap to the world of algorithm design. The authors provide motivating examples of problems faced in the real world and guide the reader to develop workable solutions, with a number of challenging exercises to promote deeper understanding." JEFFREY S. VITTER, UNIVERSITY OF KANSAS DidYouKnow? This book is available as a Wiley E-Text. The Wiley E-Text is a complete digital version of the text that makes time spent studying more efficient. Course materials can be accessed on a desktop, laptop, or mobile device--so that learning can take place anytime, anywhere. A more affordable alternative to traditional print, the Wiley E-Text creates a flexible user experience: * Access on-the-go * Search across content * Highlight and take notes * Save money! The Wiley E-Text can be purchased in the following ways: Via your campus bookstore: Wiley E-Text: Powered by VitalSource(R) ISBN 9781119028796 *Instructors: This ISBN is needed when placing an order. Directly from: www.wiley.com/college/goodrich
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.
Inhaltsangabe
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
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. UsefulMathematical Facts
Bibliography
Index
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