Compared to What?: An Introduction to the Anaylsis of Algorithms (Principles of Computer Science Series)

Rawlins, Gregory J.E.

ISBN 10: 071678243X / ISBN 13: 9780716782438

Published by W. H. Freeman, 1991

About this Item

Item in very good condition! Textbooks may not include supplemental items i.e. CDs, access codes etc.

Seller Inventory # 00079731281

Bibliographic Details

• Title: Compared to What?: An Introduction to the Anaylsis of Algorithms (Principles of Computer Science Series)
• Publisher: W. H. Freeman
• Publication Date: 1991
• Language: English
• ISBN 10: 071678243X
• ISBN 13: 9780716782438
• Binding: Hardcover
• Condition: Good

About this title

Synopsis

compared to what? covers all the basics of algorithm analysis but it does not just supply algorithms to memorize - it lets you guide your students through the process of breaking down and solving aigolithmic problems. The invaluable analytic skills developed through this innovative approach will appiv to anj, programming assignment-no matter the size of the problem or the language and macnine used. The book does not assume a high degree of familiarity with discrete mathematics-in fact, all mathematical concepts crucial to algorithm analysis are explained in the appendices. Each chapter centers on a basic problem and works through a variety of available . options for its solution rather than declaring a single best answer. Within the chapters, carefully orchestrated. 'Pauses'-helpful questions and strategy suggestions-point students to workable solutions and to increasinglv more advanced variations and applications. End-of-chapter 'Codas' restate each chapter's major themes and guide the transition into the next set of problems. Compared to What? will help students analyze problems, determine what needs to be optimized, and pinpoint inefficiencies and inaccuracies in their programs. Its fr-iendlv but challenging style, inventive examples 'and analogies, descriptions of state-of-the-art applications, and pragmatic focus will help you teach students to create algorithmic solutions-not merely memorize them.