Data Structures and Algorithm Analysis in Java, 3rd Edition

01/25/2012 · No Responses

Data Structures and Algorithm Analysis in Java is an “advanced algorithms” book that fits between traditional CS2 and Algorithms Analysis courses. In the old ACM Curriculum Guidelines, this course was known as CS7. This text is for readers who want to learn good programming and algorithm analysis skills simultaneously so that they can develop such programs with the maximum amount of efficiency. Readers should have some knowledge of intermediate programming, including topics as object-based programming and recursion, and some background in discrete math.

As the speed and power of computers increases, so does the need for effective programming and algorithm analysis. By approaching these skills in tandem, Mark Allen Weiss teaches readers to develop well-constructed, maximally efficient programs in Java.

Weiss clearly explains topics from binary heaps to sorting to NP-completeness, and dedicates a full chapter to amortized analysis and advanced data structures and their implementation. Figures and examples illustrating successive stages of algorithms contribute to Weiss’ careful, rigorous and in-depth analysis of each type of algorithm. A logical organization of topics and full access to source code complement the text’s coverage.

From the Back Cover
Mark Allen Weiss provides a proven approach to algorithms and data structures using the exciting Java programming language as the implementation tool. With Java he highlights conceptual topics, focusing on ADTs and the analysis of algorithms for efficiency as well as performance and running time. Dr. Weiss also distinguishes this text with a logical organization of topics, his engaging writing style, and an extensive use of figures and examples showing the successive stages of an algorithm.

Features

Contains extensive sample code using Java 1.2, which is available over the Internet.
Covers the Java Collections Library in an appendix.
Includes a chapter on algorithm and design techniques that covers greedy algorithms, divide-and-conquer algorithms, dynamic programming,
randomized algorithms, and backtracking.
Presents current topics and new data structures such as Fibonacci heaps, skew heaps, binomial queues, skip lists, and splay trees.
Offers a chapter on amortized analysis that examines the advanced data structures presented earlier in the book.
Provides a chapter on advanced data structures and their implementation, covering red-black trees, top-down splay trees, treaps, k-d trees, pairing heaps, and more.