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Computer algorithms : introduction to design and analysis / Sara Baase, Allen Van Gelder

By: Baase, Sara.
Contributor(s): Van Gelder, Allen [(j.a)].
Publisher: Reading, Mass. : Addison-Wesley, c2000Edition: 3rd ed.Description: xix, 688 p. ; 25 cm.ISBN: 0201612445.Subject(s): Computer algorithmsDDC classification: 519.7
Contents:
Preface. - 1. Analyzing Algorithms and Problems : Principles and Examples. - 2. Data Abstraction and Basic Data Structures. - 3. Recursion and Induction. - 4. Sorting. - 5. Selection and Adversary Arguments. - 6. Dynamic Sets and Searching. - 7. Graphs and Graph Traversals. - 8. Graph Optimization Problems and Greedy Algorithms. - 9. Transitive Closure, All-Pairs Shortest Paths. - 10. Dynamic Programming. - 11. String Matching. - 12. Polynomials and Matrices. - 13. NP-Complete Problems. - 14. Parallel Algorithms. - A. Java Examples and Techniques. - Bibliography. - Index.
Summary: This book is intended for an upper-division or graduate course in algorithms. It has sufficient material to allow several choices of topics. The purpose of the book is threefold. It is intended to teach algorithms for solving real problems that arise frequently in computer applications, to teach basic principles and techniques of computational complexity (worst-case and average behaviour, space usage, and lower bounds on the complexity of a problem), and to introduce the areas of NP-completeness and parallel algorithms. - Preface
Item type Current location Call number Copy number Status Notes Date due Barcode Remark
Main Collection TU External Storage-LCS
519.7 BAA (Browse shelf) 1 Available SOCIT,15009,03,GR 1000109947 Please fill up online form at https://taylorslibrary.taylors.edu.my/services/external_storage1

Preface. - 1. Analyzing Algorithms and Problems : Principles and Examples. - 2. Data Abstraction and Basic Data Structures. - 3. Recursion and Induction. - 4. Sorting. - 5. Selection and Adversary Arguments. - 6. Dynamic Sets and Searching. - 7. Graphs and Graph Traversals. - 8. Graph Optimization Problems and Greedy Algorithms. - 9. Transitive Closure, All-Pairs Shortest Paths. - 10. Dynamic Programming. - 11. String Matching. - 12. Polynomials and Matrices. - 13. NP-Complete Problems. - 14. Parallel Algorithms. - A. Java Examples and Techniques. - Bibliography. - Index.

This book is intended for an upper-division or graduate course in algorithms. It has sufficient material to allow several choices of topics. The purpose of the book is threefold. It is intended to teach algorithms for solving real problems that arise frequently in computer applications, to teach basic principles and techniques of computational complexity (worst-case and average behaviour, space usage, and lower bounds on the complexity of a problem), and to introduce the areas of NP-completeness and parallel algorithms. - Preface