Now revised to reflect the innovations of Java 5.0, Goodrich and Tamassia’s Fourth Edition of Data Structures and Algorithms in Javacontinues to offer accessible coverage of fundamental data structures, using a consistent object-oriented framework. The authors provide intuition, description, and analysis of fundamental data structures and algorithms. Numerous illustrations, web-based animations, and simplified mathematical analyses justify important analytical concepts.

Key Features of the Fourth Edition:

• Updates to Java 5.0 include new sections on generics and other Java 5.0 features, and revised code fragments, examples, and case studies to conform to Java 5.0.
• Hundreds of exercises, including many that are new to this edition, promote creativity and help readers learn how to think like programmers and reinforce important concepts.
• New case studies illustrate topics such as web browsers, board games, and encryption.
• A new early chapter covers Arrays, Linked Lists, and Recursion.
• A new final chapter on Memory covers memory management and external memory data structures and algorithms.
• Java code examples are used extensively, with source code provided on the website.
• Online animations and effective in-text art illustrate data structures and algorithms in a clear, visual manner.

Access additional resources on the web www.wiley.com/college/goodrich):

• Java source code for all examples in the book
• Animations
• Library (net.datastructures) of Java constructs used in the book
• Problems database and search engine
• Student hints to all exercises in the book
• Instructor resources, including solutions to selected exercises
• Lecture slides

* Presents new figures, simpler language, and more practical motivations from real-world scenarios

* Numerous illustrations, Web-based animations, and simplified mathematical analyses help readers quickly learn important concepts

Michael Goodrich received his Ph.D. in Computer Science from Purdue University in 1987. He is currently a professor in the Department of Computer Science at University of California, Irvine. Previously, he was a professor at Johns Hopkins University. He is an editor for the International Journal of Computational Geometry & Applications and Journal of Graph Algorithms and Applications.

Roberto Tamassia received his Ph.D. in Electrical and Computer Engineering from the University of Illinois at Urbana-Champaign in 1988. He is currently a professor in the Department of Computer Science at Brown University. He is editor-in-chief for the Journal of Graph Algorithms and Applications and an editor for Computational Geometry: Theory and Applications. he previously served on the editorial board of IEEE Transactions on Computers.

In addition to their research accomplishments, the authors also have extensive experience in the classroom. For example, Dr. Goodrich has taught data structures and algorithms courses, including Data Structures as a freshman-sophomore level course and Introduction to Algorithms as an upper level course. He has earned several teaching wards in this capacity. His teaching style is to involve the students in lively interactive classroom session that bring out the intuition and insights behind data structuring and algorithmic techniques. Dr. Tamassia has taught Data Structures and Algorithms as an introductory freshman-level course since 1988. One thing that has set his teaching style apart is his effective use of interactive hypermedia presentations integrated with the Web.

This instructional Web sites, datastructures.net and algorithmdesign.net, supported by Drs. Goodrich and Tamassia, are used as reference material by students, teachers, and professionals worldwide.

2. Object-Oriented Design.

3. Arrays, Linked Lists, and Recursion.

4. Analysis Tools.

5. Stacks and Queues.

6. Lists and Iterators.

7. Trees.

8. Priority Queues.

9. Maps and Dictionaries.

10. Search Trees.

11. Sorting, Sets, Selection.

12. Text Processing.

13. Graphs.

14. Memory.

Appendix: Useful Mathematical Facts.

Bibliography.

Index.