Algorithms
United States Edition
Published on 28. August 2003
Book
Hardback
768 pages
978-0-02-360692-2 (ISBN)
Description
For upper-level undergraduate and graduate courses in algorithms.
Filling the void left by other algorithms books, Algorithms and Data Structures provides an approach that emphasizes design techniques. The text includes application of algorithms, examples, end-of-section exercises, end-of-chapter exercises, hints and solutions to selected exercises, figures and notes to help the reader master the design and analysis of algorithms.
Filling the void left by other algorithms books, Algorithms and Data Structures provides an approach that emphasizes design techniques. The text includes application of algorithms, examples, end-of-section exercises, end-of-chapter exercises, hints and solutions to selected exercises, figures and notes to help the reader master the design and analysis of algorithms.
More details
Other editions
New editions
Book
08/2003
Pearson
€152.26
Article is exhausted; no reprint
Persons
Richard Johnsonbaugh is Professor Emeritus of Computer Science at DePaul University. He has degrees in computer science and mathematics from the University of Oregon, Yale University, and the University of Illinois at Chicago. He is the author of numerous articles and books, including Discrete Mathematics, Fifth Edition, and, with co-author Martin Kalin, Object-Oriented Programming in C++, Second Edition, Applications Programming in C++, and Applications Programming in ANSI C, Third Edition.
Marcus Schaefer is Assistant Professor of Computer Science at DePaul University. He holds degrees in computer science and mathematics from the University of Chicago and the Universitat Karlsruhe. He has authored and co-authored several articles on complexity theory, computability, and graph theory.
Marcus Schaefer is Assistant Professor of Computer Science at DePaul University. He holds degrees in computer science and mathematics from the University of Chicago and the Universitat Karlsruhe. He has authored and co-authored several articles on complexity theory, computability, and graph theory.
Content
1. Mathematical Prerequisites.
2. Data Structures.
3. Searching Techniques.
4. Divide-and-Conquer.
5. Sorting and Selection.
6. Greedy Algorithms.
7. Dynamic Programming.
8. Text Searching.
9. Computational Algebra.
10. P and NP.
11. Coping with NP-Completeness.
12. Parallel Algorithms.
References.
Solutions to Selected Exercises.
Index.
2. Data Structures.
3. Searching Techniques.
4. Divide-and-Conquer.
5. Sorting and Selection.
6. Greedy Algorithms.
7. Dynamic Programming.
8. Text Searching.
9. Computational Algebra.
10. P and NP.
11. Coping with NP-Completeness.
12. Parallel Algorithms.
References.
Solutions to Selected Exercises.
Index.