Algorithm Design with Haskell

Ideal for learning or reference, this book explains the five main principles of algorithm design and their implementation in Haskell.

Richard Bird (Author), Jeremy Gibbons (Author)

9781108491617, Cambridge University Press

Hardback, published 9 July 2020

450 pages, 28 b/w illus. 290 exercises
25.2 x 17.8 x 2.9 cm, 0.93 kg

'I strongly suspect that Richard Bird hides a magically productive book writing apparatus in his office. This time around, Bird pulled the machine's levers together with Jeremy Gibbons and out came Algorithm Design with Haskell, a book that is remarkable in many ways … the authors recast a number of classical problems in terms of thinning, including ones like knapsack which otherwise have been tackled via dynamic programming for ages. These fresh – very confidently and competently presented- takes on established material are true highlights of the text.' Torsten Grust, Journal of Functional Programming

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.

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.

Subject Areas: Computer science [UY], Programming & scripting languages: general [UMX], Functional programming [UMJ], Algorithms & data structures [UMB]