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Algorithm Design with Haskell

Algorithm Design with Haskell

by Richard Bird, Jeremy Gibbons


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This book is devoted to five main principles of algorithm design: divide and conquer, greedy algorithms, thinning, dynamic programming, and exhaustive search. These principles are presented using Haskell, a purely functional language, leading to simpler explanations and shorter programs than would be obtained with imperative languages. Carefully selected examples, both new and standard, reveal the commonalities and highlight the differences between algorithms. The algorithm developments use equational reasoning where applicable, clarifying the applicability conditions and correctness arguments. Every chapter concludes with exercises (nearly 300 in total), each with complete answers, allowing the reader to consolidate their understanding and apply the techniques to a range of problems. The book serves students (both undergraduate and postgraduate), researchers, teachers, and professionals who want to know more about what goes into a good algorithm and how such algorithms can be expressed in purely functional terms.

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Product Details

ISBN-13: 9781108491617
Publisher: Cambridge University Press
Publication date: 07/09/2020
Pages: 450
Sales rank: 1,019,494
Product dimensions: 7.01(w) x 9.92(h) x 1.14(d)

About the Author

Richard Bird is the author of a number of well-received books on Haskell, including Thinking Functionally with Haskell (Cambridge, 2015) and Pearls of Functional Algorithm Design (Cambridge, 2010). He retired in 2008 and is now an Emeritus Professor at the University of Oxford.

Jeremy Gibbons is Professor of Computing at the University of Oxford, where he teaches on the part-time professional Master's programme in software engineering. He is joint Editor-in-Chief of the Journal of Functional Programming, past Chair of IFIP Working Group 2.1 on Algorithmic Languages and Calculi, and past Vice-Chair of ACM SIGPLAN.

Table of Contents

Part I. Basics: 1. Functional programming; 2. Timing; 3. Useful data structures; Part II. Divide and conquer: 4. Binary search; 5. Sorting; 6. Selection; Part III. Greedy algorithms: 7. Greedy algorithms on lists; 8. Greedy algorithms on trees; 9. Greedy algorithms on graphs; Part IV. Thinning algorithms: 10. Introduction to thinning; 11. Segments and subsequences; 12. Partitions; Part V. Dynamic programming: 13. Efficient recursions; 14. Optimum bracketing; Part VI. Exhaustive search: 15. Ways of searching; 16. Heuristic search; Index.

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