Data Structures and Algorithms in Java 3E Wiley International Edition
* Entirely new chapter on recursion
* Additional exercises on the analysis of simple algorithms
* New case study on parenthesis matching and HTML validation
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 awards in this capacity. His teaching style is to involve the students in lively interactive classroom sessions 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.
Table of Contents
2. Object-Oriented Design.
3. Analysis Tools.
4. Stacks, Queues, and Recursion.
5. Vectors, Lists, and Sequences.
7. Priority Queues.
8. Maps and Dictionaries.
9. Search Trees.
10. Sorting, Sets and Selection.
11. Text Processing.
Appendix: Useful Mathematical Facts.
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