Combinatorics for Computer Science (Computers and math series) by Williamson, S. Gill (1985) Hardcover

by S. Gill Williamson

Book Overview

Useful guide covers two major subdivisions of combinatorics - enumeration and graph theory - with emphasis on conceptual needs of computer science. Each part is divided into a "basic concepts" chapter... This description may be from another edition of this product.

• Format: Hardcover
• Language: English
• ISBN: 0881750204
• ISBN13: 9780881750201
• Release Date: January 1985
• Publisher: Computer Science Press
• Length: 479 Pages
• Weight: 0.05 lbs.

Customer Reviews

Suitable for a graduate level course

While most computer science departments require their students to take calculus, with few exceptions it is a skill that they will not use. The mathematics used by computer scientists is almost exclusively discrete in nature. In fact, assumptions concerning continuity can often lead to subtle errors in programming, the laws of algebra do not universally apply in computing. This book presents most of the key ideas of discrete mathematics applied to computing and the coverage is thorough and detailed. It is split into two parts, linear order and graphs, trees and recursion. The emphasis is on detailed problem solving rather than explanations of the foundations. For example, there is a detailed example of a lexicographic bucket sort on page 16. The material is presented using higher level mathematical notation, so it is best suited for graduate level courses. A large number of exercises are included, but no solutions are given. If you are looking for a text to be used in classes that have significant discrete mathematics prerequisites, then this book is certainly appropriate. It would be best suited for students with a great deal of programming experience.

Excellent reference for data structure algorithm complexity.

This excellent reference has numerous examples, definitions and exercises covering trees, graphs, linked lists etc. This book provides a great companion to any data structures text.