The Algorithm Design Manual - Steven S Skiena

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Résumé :
This newly expanded and updated second edition of the best-selling classic continues to take the mystery out of designing algorithms, and analyzing their efficacy and efficiency. Expanding on?the first edition, the book now serves as the primary textbook of choice for algorithm design courses while maintaining its status as the premier practical reference guide to algorithms for programmers, researchers, and students.The reader-friendly?Algorithm Design Manual?provides straightforward access to combinatorial algorithms technology, stressing design over analysis. The first part,?Techniques, provides accessible instruction?on methods for designing and analyzing computer algorithms. The second part,?Resources, is intended for browsing and reference, and comprises the catalog of algorithmic resources, implementations and an extensive bibliography.

NEW?to the second edition:

.?Doubles the tutorial material and exercises?over the first edition
. Provides?full online support?for lecturers, and a?completely updated and improved?website component with lecture slides, audio and video. Contains a?unique catalog?identifying the 75 algorithmic problems that arise most often in practice, leading the reader down the right path to solve them

. Includes several?NEW?war stories relating experiences from?real-world applications.?Provides up-to-date links leading to the very best algorithm?implementations?available in C, C++, and Java

Biographie:
Steven Skiena is Professor of Computer Science at Stony Brook University. His research interests include the design of graph, string, and geometric algorithms, and their applications (particularly to biology). He is the author of four books, including The Algorithm Design Manual and Calculated Bets: Computers, Gambling, and Mathematical Modeling to Win. He is recipient of the ONR Young Investigator Award and the IEEE Computer Science and Engineering Undergraduate Teaching Award.

Sommaire:
Part I: Practical Algorithm Design. Introduction to Algorithms. Algorithm Analysis. Data Structures. Sorting and Searching. Graph Traversal. Weighted Graph Algorithms. Combinatorial Search and Heuristic Methods. Dynamic Programming. Intractable Problems and Approximations. How to Design Algorithms.- Part II: The Hitchhiker's Guide to Algorithms. A Catalog of Algorithmic Problems. Data Structures. Numerical Problems. Combinatorical Problems. Graph Problems: Polynomial-Time. Graph Problems: Hard Problems. Computational Geometry. Set and String Problems. Algorithmic Resources.- Bibliography.- Index.