Data Structures and Algorithms in C++ / Edition 2

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More About This Textbook

Overview

An updated, innovative approach to data structures andalgorithms

Written by an author team of experts in their fields, thisauthoritative guide demystifies even the most difficultmathematical concepts so that you can gain a clear understanding ofdata structures and algorithms in C++.

The unparalleled author team incorporates the object-orienteddesign paradigm using C++ as the implementation language, whilealso providing intuition and analysis of fundamentalalgorithms.

  • Offers a unique multimedia format for learning the fundamentalsof data structures and algorithms
  • Allows you to visualize key analytic concepts, learn about themost recent insights in the field, and do data structuredesign
  • Provides clear approaches for developing programs
  • Features a clear, easy-to-understand writing style that breaksdown even the most difficult mathematical concepts

Building on the success of the first edition, this new versionoffers you an innovative approach to fundamental data structuresand algorithms.

Read More Show Less

Product Details

  • ISBN-13: 9780470383278
  • Publisher: Wiley
  • Publication date: 2/22/2011
  • Edition description: New Edition
  • Edition number: 2
  • Pages: 744
  • Sales rank: 559,808
  • Product dimensions: 7.50 (w) x 9.10 (h) x 1.10 (d)

Table of Contents

1. A C++ Primer.

1.1 Basic C++ Programming Elements.

1.2 Expressions.

1.3 Control Flow.

1.4 Functions.

1.5 Classes.

1.6 C++ Program and File Organization.

1.7 Writing a C++ Program.

1.8 Exercises.

2. Object-Oriented Design.

2.1 Goals, Principles, and Patterns.

2.2 Inheritance and Polymorphism.

2.3 Templates.

2.4 Exceptions.

2.5 Exercises.

3. Arrays, Linked Lists, and Recursion.

3.1 Using Arrays.

3.2 Singly Linked Lists.

3.3 Doubly Linked Lists.

3.4 Circularly Linked and List Reversal.

3.5 Recursion.

3.6 Exercises.

4. Analysis Tools.

4.1 The Seven Functions Used in This Book.

4.2 Analysis of Algorithms.

4.3 Simple Justification Techniques.

4.4 Exercises.

5. Stacks, Queues, and Deques.

5.1 Stacks.

5.2 Queues.

5.3 Double-Ended Queues.

5.4 Exercises.

6. List and Iterator ADTs.

6.1 Vectors.

6.2 Lists.

6.3 Sequences.

6.4 Case Study: Bubble-Sort on a Sequence.

6.5 Exercises.

7. Trees.

7.1 General Trees.

7.2 Tree Traversal Algorithms.

7.3 Binary Trees.

7.4 Exercises.

8. Heaps and Priority Queues.

8.1 The Priority Queue Abstract Data Type.

8.2 Implementing a Priority Queue with a List.

8.3 Heaps.

8.4 Adaptable Priority Queues.

8.5 Exercises.

9. Hash Tables, Maps, and Skip Lists.

9.1 Maps.

9.2 Hash Tables.

9.3 Ordered Maps.

9.4 Skip Lists.

9.5 Dictionaries.

9.6 Exercises.

10. Search Trees.

10.1 Binary Search Trees.

10.2 AVL Trees.

10.3 Splay Trees.

10.4 (2,4) Trees.

10.5 Red-Black Trees.

10.6 Exercises.

11. Sorting, Sets, and Selection.

11.1 Merge-Sort.

11.2 Quick-Sort.

11.3 Studying Sorting through and Algorithmic Lens.

11.4 Sets and Union/Find Structures.

11.5 Selection.

11.6 Exercises.

12. Strings and Dynamic Programming.

12.1 String Operations.

12.2 Dynamic Programming.

12.3 Pattern Matching Algorithms.

12.4 Text Compression and the Greedy Method.

12.5 Tries.

12.6 Exercises.

13. Graph Algorithms.

13.1 Graphs.

13.2 Data Structures for Graphs.

13.3 Graph Traversals.

13.4 Directed Graphs.

13.5 Shortest Paths.

13.6 Minimum Spanning Trees.

13.7 Exercises.

14. Memory Management and B-Trees.

14.1 Memory Management.

14.2 External Memory and Caching.

14.3 External Searching and B-Trees.

14.4 External-Memory Sorting.

14.5 Exercises.

A Useful Mathematical Facts.

Bibliography.

Index. 

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