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Algorithm Design with Haskell [Hardback]

4.43/5 (13 ratings by Goodreads)

Jeremy Gibbons (University of Oxford), Richard Bird (University of Oxford)

Formāts: Hardback, 450 pages, height x width x depth: 252x178x29 mm, weight: 930 g, Worked examples or Exercises; 3 Halftones, black and white; 25 Line drawings, black and white
Izdošanas datums: 09-Jul-2020
Izdevniecība: Cambridge University Press
ISBN-10: 1108491618
ISBN-13: 9781108491617

Citas grāmatas par šo tēmu:

Computer science - (Noliktavā: 21 punkts)
Functional programming
Programming & scripting languages: general - (Noliktavā: 3 punkts)
Algorithms & data structures

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Formāts: Hardback, 450 pages, height x width x depth: 252x178x29 mm, weight: 930 g, Worked examples or Exercises; 3 Halftones, black and white; 25 Line drawings, black and white
Izdošanas datums: 09-Jul-2020
Izdevniecība: Cambridge University Press
ISBN-10: 1108491618
ISBN-13: 9781108491617

Citas grāmatas par šo tēmu:

Computer science - (Noliktavā: 21 punkts)
Functional programming
Programming & scripting languages: general - (Noliktavā: 3 punkts)
Algorithms & data structures

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Permanent link: https://www.kriso.ee/db/9781108491617.html

Keywords:

"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 simplerexplanations 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"--

Recenzijas

'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

Papildus informācija

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

Preface

xiii

PART ONE BASICS

(58)

1 Functional programming

(20)

1.1 Basic types and functions

(2)

1.2 Processing lists

(2)

1.3 Inductive and recursive definitions

(2)

1.4 Fusion

(3)

1.5 Accumulating and tupling

(2)

1.6
Chapter notes

(1)

References

(1)

Exercises

(3)

Answers

(6)

2 Timing

(18)

2.1 Asymptotic notation

(2)

2.2 Estimating running times

(5)

2.3 Running times in context

(2)

2.4 Amortised running times

(4)

2.5
Chapter notes

(1)

References

(1)

Exercises

(2)

Answers

(3)

3 Useful data structures

(16)

3.1 Symmetric lists

(4)

3.2 Random-access lists

(4)

3.3 Arrays

(2)

3.4
Chapter notes

(1)

References

(1)

Exercises

(2)

Answers

(3)

PART TWO DIVIDE AND CONQUER

(82)

4 Binary search

(30)

4.1 A one-dimensional search problem

(4)

4.2 A two-dimensional search problem

(6)

4.3 Binary search trees

(8)

4.4 Dynamic sets

(3)

4.5
Chapter notes

(1)

References

(1)

Exercises

(2)

Answers

(6)

5 Sorting

(28)

5.1 Quicksort

(2)

5.2 Mergesort

(5)

5.3 Heapsort

101

(1)

5.4 Bucketsort and Radixsort

102

(4)

5.5 Sorting sums

106

(4)

5.6
Chapter notes

110

(1)

References

110

(1)

Exercises

111

(3)

Answers

114

(7)

6 Selection

121

(20)

6.1 Minimum and maximum

121

(3)

6.2 Selection from one set

124

(4)

6.3 Selection from two sets

128

(4)

6.4 Selection from the complement of a set

132

(3)

6.5
Chapter notes

135

(1)

References

135

(1)

Exercises

135

(2)

Answers

137

(4)

PART THREE GREEDY ALGORITHMS

141

(96)

7 Greedy algorithms on lists

145

(32)

7.1 A generic greedy algorithm

145

(2)

7.2 Greedy sorting algorithms

147

(4)

7.3 Coin-changing

151

(5)

7.4 Decimal fractions in Tr-jX

156

(5)

7.5 Nondeterministic functions and refinement

161

(4)

7.6 Summary

165

(1)

7.7
Chapter notes

165

(1)

References

166

(1)

Exercises

166

(4)

Answers

170

(7)

8 Greedy algorithms on trees

177

(28)

8.1 Minimum-height trees

177

(10)

8.2 Huffman coding trees

187

(9)

8.3 Priority queues

196

(3)

8.4
Chapter notes

199

(1)

References

199

(1)

Exercises

199

(2)

Answers

201

(4)

9 Greedy algorithms on graphs

205

(32)

9.1 Graphs and spanning trees

205

(3)

9.2 Kruskal's algorithm

208

(3)

9.3 Disjoint sets and the union-find algorithm

211

(4)

9.4 Prim's algorithm

215

(4)

9.5 Single-source shortest paths

219

(1)

9.6 Dijkstra's algorithm

220

(4)

9.7 The jogger's problem

224

(4)

9.8
Chapter notes

228

(1)

References

228

(1)

Exercises

229

(2)

Answers

231

(6)

PART FOUR THINNING ALGORITHMS

237

(72)

10 Introduction to thinning

241

(26)

10.1 Theory

241

(3)

10.2 Paths in a layered network

244

(4)

10.3 Coin-changing revisited

248

(4)

10.4 The knapsack problem

252

(3)

10.5 A general thinning algorithm

255

(2)

10.6
Chapter notes

257

(1)

References

257

(1)

Exercises

257

(4)

Answers

261

(6)

11 Segments and subsequences

267

(22)

11.1 The longest upsequence

267

(3)

11.2 The longest common subsequence

270

(4)

11.3 A short segment with maximum sum

274

(6)

11.4
Chapter notes

280

(1)

References

281

(1)

Exercises

281

(2)

Answers

283

(6)

12 Partitions

289

(20)

12.1 Ways of generating partitions

289

(2)

12.2 Managing two bank accounts

291

(3)

12.3 The paragraph problem

294

(5)

12.4
Chapter notes

299

(1)

References

300

(1)

Exercises

300

(3)

Answers

303

(6)

PART FIVE DYNAMIC PROGRAMMING

309

(56)

13 Efficient recursions

313

(22)

13.1 Two numeric examples

313

(3)

13.2 Knapsack revisited

316

(3)

13.3 Minimum-cost edit sequences

319

(3)

13.4 Longest common subsequence revisited

322

(1)

13.5 The shuttle-bus problem

323

(3)

13.6
Chapter notes

326

(1)

References

326

(1)

Exercises

327

(3)

Answers

330

(5)

14 Optimum bracketing

335

(30)

14.1 A cubic-time algorithm

336

(3)

14.2 A quadratic-time algorithm

339

(2)

14.3 Examples

341

(4)

14.4 Proof of monotonicity

345

(2)

14.5 Optimum binary search trees

347

(2)

14.6 The Garsia-Wachs algorithm

349

(9)

14.7
Chapter notes

358

(1)

References

358

(1)

Exercises

359

(3)

Answers

362

(3)

PART SIX EXHAUSTIVE SEARCH

365

(67)

15 Ways of searching

369

(36)

15.1 Implicit search and the rc-queens problem

369

(7)

15.2 Expressions with a given sum

376

(2)

15.3 Depth-first and breadth-first search

378

(5)

15.4 Lunar Landing

383

(3)

15.5 Forward planning

386

(3)

15.6 Rush Hour

389

(4)

15.7
Chapter notes

393

(1)

References

394

(1)

Exercises

395

(3)

Answers

398

(7)

16 Heuristic search

405

(27)

16.1 Searching with an optimistic heuristic

406

(5)

16.2 Searching with a monotonic heuristic

411

(4)

16.3 Navigating a warehouse

415

(4)

16.4 The 8-puzzle

419

(6)

16.5
Chapter notes

425

(1)

References

425

(1)

Exercises

426

(2)

Answers

428

(4)

Index

432

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.

Algorithm Design with Haskell [Hardback]

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