An edition of Algorithms and data structures (2008)

Algorithms and data structures

the basic toolbox

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October 4, 2021 | History
An edition of Algorithms and data structures (2008)

Algorithms and data structures

the basic toolbox

  • 0 Ratings
  • 1 Want to read
  • 0 Currently reading
  • 0 Have read

The design and analysis of basic algorithms that should be part of every programmer's toolkit.

Publish Date
Publisher
Springer
Language
English
Pages
300

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Previews available in: English

Edition Availability
Cover of: Algorithms and data structures
Algorithms and data structures: the basic toolbox
2008, Springer
Hardcover in English

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Book Details


Table of Contents

1. Appetizer: Integer Arithmetics Page 1 1.1. Addition Page 2 1.2. Multiplication: The School Method Page 3 1.3. Result Checking Page 6 1.4. A Recursive version of the School Method Page 7 1.5. Karatsuba Multiplication Page 9 1.6. Algorithm Engineering Page 11 1.7. The Programs Page 13 1.8. Proofs of Lemma 1.5 and Theorem 1.7 Page 16
1.9. Implementation Notes
1.10. Historical Notes and Further Findings Page 18 2. Introduction Page 19 2.1. Asymptotic Notation Page 19 2.2. The Machine Model Page 20 2.3. Pseudocode Page 23 2.4. Designing Correct Algorithms and Programs Page 31 2.5. An Example - Binary Search Page 34 2.6. Basic Algorithm Analysis Page 41 2.7. Average-Case Analysis Page 36 2.8. Randomized Algorithms Page 45 2.9. Graphs Page 49 2.10. P and NP Page 49 2.11. Implementation Notes Page 56 2.12. Historical Notes and Further Findings Page 57 3. Representing Sequences by Arrays and Linked Lists Page 59 3.1. Linked Lists Page 60 3.2. Unbounded Arrays Page 66 3.3. *Amortized Analysis Page 71 3.4. Stacks and Queues Page 74 3.5. Lists Versus Arrays Page 77 3.6. Implementation Notes Page 78 3.7. Historical Notes and Further Findings Page 79 4. Hash Tables and Associative Arrays Page 81 4.1. Hashing and Chaining Page 83 4.2. Universal Hashing Page 85 4.3. Hashing with Linear Probing Page 90 4.4. Chaining Versus Linear Probing Page 92 4.5. *Perfect Hashing Page 92 4.6. Implementation Notes Page 95 4.7. Historical Notes and Further Findings Page 97 5. Sorting and Selection Page 99 5.1. Simple Sorters Page 101 5.2. Mergesort - an O(n log n) Sorting Algorithm Page 103 5.3. A Lower Bound Page 106 5.4. Quicksort Page 108 5.5. Selection Page 114 5.6. Breaking the Lower Bound Page 116 5.7. *External Sorting Page 118 5.8. Implementation Notes Page 122 5.9. Historical Notes and Further Findings Page 124 6. Priority Queues Page 127 6.1. Binary Heaps Page 129 6.2. Addressable Priority Queues Page 133 6.3. *External Memory Page 139 6.4. Implementation Notes Page 141 6.5. Historical Notes and Further Findings Page 142 7. Sorted Sequences Page 145 7.1. Binary Search Trees Page 147 7.2. (a, b)-Trees and Red-Black Trees Page 149 7.3. More Operations Page 156 7.4. Amortized Analysis of Update Operations Page 158 7.5. Augmented Search Trees Page 160 7.6. Implementation Notes Page 162 7.7. Historical Notes and Further Findings Page 164 8. Graph Representation Page 167 8.1. Unordered Edge Sequences Page 168 8.2. Adjacency Arrays - Static Graphs Page 168 8.3. Adjacency Lists - Dynamic Graphs Page 170 8.4. The Adjacency Matrix Representation Page 171 8.5. Implicit Representations Page 172 8.6. Implementation Notes Page 172 8.7. Historical Notes and Further Findings Page 174 9. Graph Traversal Page 175 9.1. Breadth-First Search Page 176 9.2. Depth-First Search Page 178 9.3. Implementation Notes Page 188 9.4. Historical Notes and Further Findings Page 189 10. Shortest Paths Page 191 10.1. From Basic Concepts to a Generic Algorithm Page 192 10.2. Directed Acyclic Graphs Page 195 10.3. Nonnegative Edge Costs (Dijkstra's Algorithm) Page 196 10.4. *Average-Case Analysis of Dijkstra's Algorithm Page 199 10.5. Monotone Integer Priority Queues Page 201 10.6. Arbitrary Edge Costs (Bellman-Ford Algorithm) Page 206 10.7. All-Pairs Shortest Paths and Node Potentials Page 207 10.8. Shortest-Path Queries Page 209 10.9. Implementation Notes Page 213 10.10. Historical Notes and Further Findings Page 214 11. Minimum Spanning Trees Page 217 11.1. Cut and Cycle Properties Page 218 11.2. The Jarnik-Prim Algorithm Page 219 11.3. Kruskal's Algorithm Page 221 11.4. The Union-Find Data Structure Page 222 11.5. *External Memory Page 225 11.6. Applications Page 228 11.7. Implementation Notes Page 231 11.8. Historical Notes and Further Findings Page 231 12. Generic Approaches to Optimization Page 233 12.1. Linear Programming - a Black-Box Solver Page 234 12.2. Greedy Algorithms - Never Look Back Page 239 12.3. Dynamic Programming - Building It Piece by Piece Page 243 12.4. Systematic Search - When in Doubt, Use Brute Force Page 246 12.5. Local Search - Think Globally, Act Locally Page 249 12.6. Evolutionary Algorithms Page 259 12.7. Implementation Notes Page 261 12.8. Historical Notes and Further Findings Page 262 A. Appendix Page 263 A.1. Mathematical Symbols Page 263 A.2. Mathematical Concepts Page 264 A.3. Basic Probability Theory Page 266 A.4. Useful Formulae Page 269 References Page 273 Index Page 285

Edition Notes

Includes bibliographical references (p. [273]-283) and index.

Published in
Berlin

Classifications

Library of Congress
QA76.9.D35 M47 2008, QA75.5-76.95

The Physical Object

Format
Hardcover
Pagination
xii, 300 p. :
Number of pages
300

ID Numbers

Open Library
OL21897978M
Internet Archive
algorithmsdatast00mehl_045
ISBN 13
9783540779773, 9783540779780
LCCN
2008926816
OCLC/WorldCat
221217367
Library Thing
7819176
Goodreads
3222432

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History

Download catalog record: RDF / JSON
October 4, 2021 Edited by ImportBot import existing book
June 28, 2019 Edited by MARC Bot import existing book
December 4, 2010 Edited by Open Library Bot Added subjects from MARC records.
July 31, 2010 Edited by 96.242.73.8 added description
December 10, 2009 Created by WorkBot add works page