How to Think About Algorithms by Jeff Edmonds
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How to Think About Algorithms
By Jeff Edmonds

How to Think About Algorithms

Loop Invariants and Recursion

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Format: Hardback

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How to Think About Algorithms by Jeff Edmonds

Book Description

This textbook, for second- or third-year students of computer science, presents insights, notations, and analogies to help them describe and think about algorithms like an expert, without grinding through lots of formal proof. Solutions to many problems are provided to let students check their progress, while class-tested PowerPoint slides are on the web for anyone running the course. By looking at both the big picture and easy step-by-step methods for developing algorithms, the author guides students around the common pitfalls. He stresses paradigms such as loop invariants and recursion to unify a huge range of algorithms into a few meta-algorithms. The book fosters a deeper understanding of how and why each algorithm works. These insights are presented in a careful and clear way, helping students to think abstractly and preparing them for creating their own innovative ways to solve problems.

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Book Details

ISBN: 9780521849319
ISBN-10: 0521849314
Format: Hardback
(253mm x 177mm x 26mm)
Pages: 472
Imprint: Cambridge University Press
Publisher: Cambridge University Press
Publish Date: 19-May-2008
Country of Publication: United Kingdom

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Books By Author Jeff Edmonds

How to Think About Algorithms by Jeff Edmonds How to Think About Algorithms, Paperback (May 2008)

Textbook that teaches students how to think about algorithms like an expert, without getting bogged down in formal proof.

» View all books by Jeff Edmonds


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Author Biography - Jeff Edmonds

Jeff Edmonds received his Ph.D. in 1992 at University of Toronto in theoretical computer science. His thesis proved that certain computation problems require a given amount of time and space. He did his postdoctorate work at the ICSI in Berkeley on secure multi-media data transmission and in 1995 became an Associate Professor in the Department of Computer Science at York University, Canada. He has taught their algorithms course thirteen times to date. He has worked extensively at IIT Mumbai, India, and University of California San Diego. He is well published in the top theoretical computer science journals in topics including complexity theory, scheduling, proof systems, probability theory, combinatorics, and, of course, algorithms.

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