Algorithm Design: Foundations, Analysis, and Internet Examples / Edition 1

Algorithm Design: Foundations, Analysis, and Internet Examples / Edition 1

by Michael T. Goodrich, Roberto Tamassia
     
 

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ISBN-10: 0471383651

ISBN-13: 9780471383659

Pub. Date: 10/15/2001

Publisher: Wiley

Michael Goodrich and Roberto Tamassia, authors of the successful, Data Structures and Algorithms in Java, 2/e, have written Algorithm Engineering, a text designed to provide a comprehensive introduction to the design, implementation and analysis of computer algorithms and data structures from a modern perspective. This book offers theoretical analysis techniques as

Overview

Michael Goodrich and Roberto Tamassia, authors of the successful, Data Structures and Algorithms in Java, 2/e, have written Algorithm Engineering, a text designed to provide a comprehensive introduction to the design, implementation and analysis of computer algorithms and data structures from a modern perspective. This book offers theoretical analysis techniques as well as algorithmic design patterns and experimental methods for the engineering of algorithms.
Market: Computer Scientists; Programmers.

Product Details

ISBN-13:
9780471383659
Publisher:
Wiley
Publication date:
10/15/2001
Pages:
720
Product dimensions:
7.50(w) x 9.25(h) x 1.47(d)

Table of Contents

I Fundamental Tools 1

1 Algorithm Analysis 3

1.1 Methodologies for Analyzing Algorithms 5

1.2 Asymptotic Notation 13

1.3 A Quick Mathematical Review 21

1.4 Case Studies in Algorithm Analysis 31

1.5 Amortization 34

1.6 Experimentation 42

1.7 Exercises 47

2 Basic Data Structures 55

2.1 Stack sand Queues 57

2.2 Vectors, Lists, and Sequences 65

2.3 Trees 75

2.4 Priority Queues and Heaps 94

2.5 Dictionaries and Hash Tables 114

2.6 Java Example: Heap 128

2.7 Exercises 131

3 Search Trees and Skip Lists 139

3.1 Ordered Dictionaries and Binary Search Trees 141

3.2 AVL Trees 152

3.3 Bounded-Depth Search Trees 159

3.4 Splay Trees 185

3.5 Sk i p Lists 195

3.6 Java Example: AVL and Red-Black Trees 202

3.7 Exercises 212

4 Sorting, Sets, and Selection 217

4.1 Merge-Sort 219

4.2 The Set Abstract Data Type 225

4.3 Quick -Sort 235

4.4 A Lower Bound on Comparison-Based Sorting 239

4.5 Buck et-Sort and Radix-Sort 241

4.6 Comparison of Sorting Algorithms 244

4.7 Selection 245

4.8 Java Example: In-Place Quick -Sort 248

4.9 Exercises 251

5 Fundamental Techniques 257

5.1 The GreedyMethod 259

5.2 Divide-and-Conquer 263

5.3 Dynamic Programming 274

5.4 Exercises 282

II Graph Algorithms 285

6 Graphs 287

6.1 The Graph Abstract Data Type 289

6.2 Data Structures for Graphs 296

6.3 Graph Traversal 303

6.4 Directed Graphs 316

6.5 Java Example: Depth-First Search 329

6.6 Exercises 335

7 Weighted Graphs 339

7.1 Single-Source Shortest Paths 341

7.2 All-Pairs Shortest Paths 354

7.3 Minimum Spanning Trees 360

7.4 Java Example: Dijk stra’s Algorithm 373

7.5 Exercises 376

8 Network Flow and Matching 381

8.1 Flows and Cuts 383

8.2 Maximum Flow 387

8.3 Maximum BipartiteMatching 396

8.4 Minimum-Cost Flow 398

8.5 Java Example: Minimum-Cost Flow 405

8.6 Exercises 412

III Internet Algorithmics 415

9 Text Processing 417

9.1 Strings and PatternMatching Algorithms 419

9.2 Tries 429

9.3 Text Compression 440

9.4 Text Similarity Testing 443

9.5 Exercises 447

10 Number Theory and Cryptography 451

10.1 Fundamental Algorithms Involving Numbers 453

10.2 Cryptographic Computations 471

10.3 Information Security Algorithms and Protocols 481

10.4 The Fast Fourier Transform 488

10.5 Java Example: FFT 500

10.6 Exercises 508

11 Network Algorithms 511

11.1 ComplexityMeasures and Models 513

11.2 Fundamental Distributed Algorithms 517

11.3 Broadcast and Unicast Routing 530

11.4 Multicast Routing 535

11.5 Exercises 541

IV Additional Topics 545

12 Computational Geometry 547

12.1 Range Trees 549

12.2 Priority Search Trees 556

12.3 Quadtrees and k-D Trees 561

12.4 The Plane Sweep Technique 565

12.5 Convex Hulls 572

12.6 Java Example: Convex Hull 583

12.7 Exercises 587

13 NP-Completeness 591

13.1 P and NP 593

13.2 NP-Completeness 599

13.3 Important NP-Complete Problems 603

13.4 Approximation Algorithms 618

13.5 Back track i ng and Branch-and-Bound 627

13.6 Exercises 638

14 Algorithmic Frameworks 643

14.1 External-Memory Algorithms 645

14.2 Parallel Algorithms 657

14.3 Online Algorithms 667

14.4 Exercises 680

A Useful Mathematical Facts 685

Bibliography 689

Index 698

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