Analysis of Algorithms An Active Learning Approach Second Edition

Updated To Follow The Recommendations Put Forth By The ACM/SIGCSE 2001 Task Force, Analysis Of Algorithms Raises Awareness Of The Effects That Algorithms Have On The Efficiency Of A Program And Develops The Necessary Skills To Analyze General Algorithms Used In Programs. The Text Presents The Material With The Expectation That It Can Be Used With Active And Cooperative Learning Methodology, Based On The Premise That Students Learn More Effectively And Retain More Information Longer When They Are Active Participants In The Learning Process. To Accomplish This, The Chapters Are Clear And Complete To Encourage Students To Prepare By Reading Before Class, And The Text Is Filled With Exciting Examples And Exercises That Look At The Efficiency Of Various Algorithms To Solve A Problem. The Author Is Well Known For Workshops That He Presents On The Active Learning Model. He Has Written An Instructor’s Manual That Helps Instructors Understand How To Present The Material In An Active Way.

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McConnell (Canisius College) developed this course to make students aware of the impact of algorithms on a program’s efficiency and instruct them in the skills to analyze algorithms used in programs. Students learn the basics of analysis; searching, selecting, and sorting algorithms; and the elements of numeric, matching, graph, parallel, nondeterministic, greedy approximation, and probabilistic algorithms. Study suggestions and programming exercises are provided for students to apply what they learn. Annotation c. Book News, Inc., Portland, OR (booknews.com)