How to Think About Algorithms
Loop Invariants and Recursion
By (author) Jeff Edmonds
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How to Think About Algorithms by Jeff Edmonds
Book DescriptionThis 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 DetailsISBN: 9780521849319
(253mm x 177mm x 26mm)
Imprint: Cambridge University Press
Publisher: Cambridge University Press
Publish Date: 19-May-2008
Country of Publication: United Kingdom
Books By Author Jeff Edmonds
How to Think About Algorithms, Paperback (May 2008)» View all books by Jeff Edmonds
Textbook that teaches students how to think about algorithms like an expert, without getting bogged down in formal proof.
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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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