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The goal of Analysis of Algorithms is to raise awareness of the effect that algorithms have on the efficiency of a program and to develop the necessary skills to analyze general algorithms used in programs. The text presents the material with the expectation that it can be used with active and cooperative learning methodology, based on the premise that students learn more effectively and retain more information longer when they are active participants in the learning process. Developed to offer students multiple opportunities for active and cooperative learning. To accomplish this, the chapters are clear and complete to encourage students to prepare by reading before class, and the text is filled with exciting examples and exercises that look at the efficiency of various algorithms to solve a problem.

Sedgewick has a real gift for explaining concepts in a way that makes them easy to understand. The use of real programs in page-size (or less) chunks that can be easily understood is a real plus. The figures, programs, and tables are a significant contribution to the learning experience of the reader; they make this book distinctive.
--William A. Ward, University of South Alabama

This edition of Robert Sedgewick's popular work provides current and comprehensive coverage of important algorithms for Java programmers. Michael Schidlowsky and Sedgewick have developed new Java implementations that both express the methods in a concise and direct manner and provide programmers with the practical means to test them on real applications.

Many new algorithms are presented, and the explanations of each algorithm are much more detailed than in previous editions. A new text design and detailed, innovative figures, with accompanying commentary, greatly enhance the presentation. The third edition retains the successful blend of theory and practice that has made Sedgewick's work an invaluable resource for more than 400,000 programmers!

This particular book, Parts 1-4, represents the essential first half of Sedgewick's complete work. It provides extensive coverage of fundamental data structures and algorithms for sorting, searching, and related applications. Although the substance of the book applies to programming in any language, the implementations by Schidlowsky and Sedgewick also exploit the natural match between Java classes and abstract data type (ADT) implementations.

Highlights:

Whether you are learning the algorithms for the first time or wish to have up-to-date reference material that incorporates new programming styles with classic and new algorithms, you will find a wealth of useful information in this book.

In addition to traditional topics, this comprehensive compendium of algorithms, data structures, and theory of computation covers:
- applications areas where algorithms and data structuring techniques are of special importance
- graph drawing
- robot algorithms
- VLSI layoutovision and image processing algorithms
- scheduling
- electronic cash
- data compression
- dynamic graph algorithms
- on-line algorithms
- multidimensional data structures
- cryptography
- advanced topics in combinatorial optimization and parallel/distributed computing

Unique coverage of Algorithms and Theory of Computation Handbook makes it an essential reference for researchers and practitioners in these applications areas.

This book presents the concepts, methods, and results that are fundamental to the science of computing. The book begins with the basic ideas of algorithms such as the structure and the methods of data manipulation, and then moves on to demonstrate how to design an accurate and efficient algorithm. Inherent limitations to algorithmic design are also discussed throughout the second part of the text. The third edition features an introduction to the object-oriented paradigm along with new approaches to computation. Anyone interested in being introduced to the theory of computer science.

Focusing on practical issues, A Programmer's Companion to Algorithm Analysis bridges the gap between algorithms and software programs. This book explains the fundamental differences between the computational model assumed for algorithms and the real architectures in which programs execute. It highlights the pitfalls that can occur when implementing an algorithm as software and offers suggestions to solve these problems. The book also explores the interactions among program, compiler, and run-time support system, contrasting this with the simpler model assumed for algorithms. Intended for software developers and programmers, it places particular emphasis on the implications of the memory hierarchy on program efficiency.