An Introduction to the Analysis of Algorithms (Psychopharmacology Monograph) - Tapa dura

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Robert Sedgewick is the William O. Baker Professor of Computer Science at Princeton University. He is a Director of Adobe Systems and has served on the research staffs at Xerox PARC, IDA, and INRIA. He earned his Ph.D from Stanford University under Donald E. Knuth.

About Philippe Flajolet The late Philippe Flajolet was a Senior Research Director at INRIA, Rocquencourt, where he created and led the ALGO research group, attracting visiting researchers from all over the world. He is celebrated for having opened new lines of research in the analysis of algorithms, having developed powerful new methods, and having solved difficult, open problems. Dr. Flajolet taught at Ecole Polytechnique and Princeton University; he also held visiting positions at Waterloo University, Stanford University, the University of Chile, the Technical  University of Vienna, IBM, and Bell Laboratories. He received several prizes, including the Grand Science Prize of UAP (1986), the Computer Science Prize of the French Academy of Sciences (1994), and the Silver Medal of CNRS (2004). He was elected a Member of the Academia Europaea in 1995 and a Member (Fellow) of the French Academy of Sciences in 2003.

Phillipe passed away suddenly and unexpectedly a few months ago.

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"People who analyze algorithms have double happiness. First of all they experience the sheer beauty of elegant mathematical patterns that surround elegant computational procedures. Then they receive a practical payoff when their theories make it possible to get other jobs done more quickly and more economically.... The appearance of this long-awaited book is therefore most welcome. Its authors are not only worldwide leaders of the field, they also are masters of exposition." --D. E. Knuth

This book provides a thorough introduction to the primary techniques used in the mathematical analysis of algorithms. The authors draw from classical mathematical material, including discrete mathematics, elementary real analysis, and combinatorics, as well as from classical computer science material, including algorithms and data structures. They focus on "average-case" or "probabilistic" analysis, although they also cover the basic mathematical tools required for "worst-case" or "complexity" analysis. Topics include recurrences, generating functions, asymptotics, trees, strings, maps, and an analysis of sorting, tree search, string search, and hashing algorithms.

Despite the large interest in the mathematical analysis of algorithms, basic information on methods and models in widespread use has not been directly accessible for work or study in the field. The authors here address this need, combining a body of material that gives the reader both an appreciation for the challenges of the field and the requisite background for keeping abreast of the new research being done to meet these challenges.

• Thorough, self-contained coverage for students and professionals in computer science and mathematics
• Focus on mathematical techniques of analysis
• Basic preparation for the advanced results covered in Knuth's books and the research literature
• Classical approaches and results in the analysis of algorithms