Data Structures and Algorithm Analysis in C++, 2/E
Mark Allen Weiss, Florida International University

ISBN-10: 0201361221
ISBN-13: 9780201361223

Publisher: Addison-Wesley
Copyright: 1999
Format: Paper; 564 pp
Status: Out of Print

Suggested retail price: $131.20
This item is out of print and is no longer available for purchase.

In this second edition of his successful book, experienced teacher and author Mark Allen Weiss continues to refine and enhance his innovative approach to algorithms and data structures. Written for the advanced data structures course, this text highlights theoretical topics like abstract data types and the efficiency of algorithms, as well as performance and running time. Before covering algorithms and data structures, the author provides a brief introduction to C++ for programmers unfamiliar with the language. All of the source code will be available over the Internet. Dr. Weiss also distinguishes the book with his clear, friendly writing style, logical organization of topics, and extensive use of figures and examples that show the successive stages of an algorithm.

  • All code has been updated and tested on multiple platforms and conforms to the ANSI standard.
  • Provides chapter on advanced structures and their implementation covering red black trees, top down splay trees, treaps, k-d trees, pairing heaps, and more.
  • Includes a chapter on algorithm and design techniques that covers greedy algorithms, divide and conquer algorithms, dynamic programming, randomized algorithms, and backtracking.



1. Introduction.

What's the Book About?

Mathematics Review.

Exponents.

Logarithms.

Series.

Modular Arithmetic.

The P Word.

A Brief Introduction to Recursion

C++ Classes.

Basic class Syntax.

Extra Constructor Syntax and Accessors

Separation of Interface and Implementation.

vector and string.

C++ Details.

Pointers.

Parameter Passing.

Return Passing

Reference Variables.

The Big Three: Destructor, Copy Constructor, operator=.

The World of C.

Templates.

Function Templates.

Class Templates.

Object, Comparable, and an Example.

Using Matrices.

The Data Members, Constructor, and Basic Accessors.

operator [ ].

Destructor, Copy Assignment, Copy Constructor.

Summary.

Exercises.

References.



2. Algorithm Analysis.

Mathematical Background.

Model.

What to Analyze.

Running Time Calculations.

A Simple Example.

General Rules.

Solutions for the Maximum Subsequence Sum Problem.

Logarithms in the Running Time.

Checking Your Analysis.

A Grain of Salt.

Summary.

Exercises.

References.



3. Lists, Stacks, and Queues.

Abstract Data Types (ADTs).

The List ADT.

Simple Array Implementation of Lists.

Linked Lists.

Programming Details.

Memory Reclamation and the Big Three.

Doubly Linked Lists.

Circular Linked Lists.

Examples.

Cursor Implementation of Linked Lists.

The Stack ADT.

Stack Model.

Implementation of Stacks.

Applications.

The Queue ADT.

Queue Model.

Array Implementation of Queues.

Applications of Queues.

Summary.

Exercises.



4. Trees.

Preliminaries.

Implementation of Trees.

Tree Traversals with an Application.

Binary Trees.

Implementation.

An Example: Expression Trees.

The Search Tree ADT-Binary Search Trees.

find.

findMin and findMax.

insert.

remove.

Destructor and Copy Assignment Operator.

Average-Case Analysis.

AVL Trees.

Single Rotation.

Double Rotation.

Splay Trees.

A Simple Idea (That Does Not Work).

Splaying.

Tree Traversals (Revisited).

B-Trees.

Summary.

Exercises.

References.



5. Hashing.

General Idea.

Hash Function.

Separate Chaining.

Open Addressing.

Linear Probing.

Quadratic Probing.

Double Hashing.

Rehashing.

Extendible Hashing.

Summary.

Exercises.

References.



6. Priority Queues (Heaps).

Model.

Simple Implementations.

Binary Heap.

Structure Property.

Heap-Order Property.

Basic Heap Operations.

Other Heap Operations.

Applications of Priority Queues.

The Selection Problem.

Event Simulation.

d-Heaps.

Leftist Heaps.

Leftist Heap Property.

Leftist Heap Operations.

Skew Heaps.

Binomial Queues.

Binomial Queue Structure.

Binomial Queue Operations.

Implementation of Binomial Queues.

Summary.

Exercises.

References.



7. Sorting.

Preliminaries.

Insertion Sort.

The Algorithm.

Analysis of Insertion Sort.

A Lower Bound for Simple Sorting Algorithms.

Shellsort.

Worst-Case Analysis of Shellsort

Heapsort.

Analysis of Heapsort.

Mergesort.

Analysis of Mergesort.

Quicksort.

Picking the Pivot.

Partitioning Strategy.

Small Arrays.

Actual Quicksort Routines.

Analysis of Quicksort

A Linear-Expected-Time Algorithm for Selection.

Indirect Sorting.

vector<Comparable *> Does Not Work.

Smart Pointer Class.

Overloading operator<

Dereferencing a Pointer with *.

Overloading the Type Conversion Operator

Implicit Type Conversions Are Everywhere.

Dual-Direction Implicit Conversions Can Cause Ambiguities.

Pointer Subtraction Is Legal.

A General Lower Bound for Sorting.

Decision Trees.

Bucket Sort.

External Sorting.

Why We Need New Algorithms.

Model for External Sorting.

The Simple Algorithm.

Multiway Merge.

Polyphase Merge.

Replacement Selection.

Summary.

Exercises.

References.



8. The Disjoint Set ADT.

Equivalence Relations.

The Dynamic Equivalence Problem.

Basic Data Structure.

Smart Union Algorithms.

Path Compression.

Worst Case for Union-by-Rank and Path Compression.

Analysis of the Union/Find Algorithm.

An Application.

Summary.

Exercises.

References.



9. Graph Algorithms.

Definitions.

Representation of Graphs.

Topological Sort.

Shortest-Path Algorithms.

Unweighted Shortest Paths.

Dijkstra's Algorithm.

Graphs with Negative Edge Costs

Acyclic Graphs.

All-Pairs Shortest Path.

Network Flow Problems.

A Simple Maximum-Flow Algorithm.

Minimum Spanning Tree.

Prim's Algorithm.

Kruskal's Algorithm.

Applications of Depth-First Search.

Undirected Graphs.

Biconnectivity.

Euler Circuits.

Directed Graphs.

Finding Strong Components.

Introduction to NP-Completeness.

Easy vs. Hard.

The Class NP.

NP-Complete Problems.

Summary.

Exercises.

References.



10. Algorithm Design Techniques.

Greedy Algorithms.

A Simple Scheduling Problem.

Huffman Codes.

Approximate Bin Packing.

Divide and Conquer.

Running Time of Divide and Conquer Algorithms.

Closest-Points Problem.

The Selection Problem.

Theoretical Improvements for Arithmetic Problems.

Dynamic Programming.

Using a Table Instead of Recursion.

Ordering Matrix Multiplications.

Optimal Binary Search Tree.

All-Pairs Shortest Path.

Randomized Algorithms.

Random Number Generators.

Skip Lists.

Primality Testing.

Backtracking Algorithms.

The Turnpike Reconstruction Problem.

Games.

Summary.

Exercises.

References.



11. Amortized Analysis.

An Unrelated Puzzle.

Binomial Queues.

Skew Heaps.

Fibonacci Heaps.

Cutting Nodes in Leftist Heaps.

Lazy Merging for Binomial Queues.

The Fibonacci Heap Operations.

Proof of the Time Bound.

Splay Trees.

Summary.

Exercises.

References.



12. Advanced Data Structures and Implementation.

Top-Down Splay Trees.

Red-Black Trees.

Bottom-Up Insertion.

Top-Down Red-Black Trees.

Top-Down Deletion.

Deterministic Skip Lists.

AA-Trees.

Treaps.

k-d Trees.

Pairing Heaps.

Summary.

Exercises.

References.



Appendix A. The Standard Template Library.

Introduction

Basic STL Concepts.

Header Files and the using Directive

Containers.

iterator.

Pairs.

Function Objects.

Unordered Sequences: vector and list.

vector versus list.

Stacks and Queues.

Sets.

Maps.

Example: Generating a Concordance.

STL Version.

Version without Using the STL

Example: Shortest-Path Calculation.

STL Implementation.

Version without Using the STL.

Other STL Features.



Appendix B. vector and string Classes.

First-Class versus Second-Class Objects.

vector Class.

string Class.



Index. 0201361221T04062001

    Mark Allen Weiss’ innovative approach to algorithms and data structures teaches the simultaneous development of sound analytical and programming skills for the advanced data structures course. Readers learn how to reduce time constraints and develop programs efficiently by analyzing the feasibility of an algorithm before it is coded.

     

    The C++ language is brought up-to-date and simplified, and the Standard Template Library is now fully incorporated throughout the text. This Third Edition also features significantly revised coverage of lists, stacks, queues, and trees and an entire chapter dedicated to amortized analysis and advanced data structures such as the Fibonacci heap.

     

    Known for its clear and friendly writing style, Data Structures and Algorithm Analysis in C++ is logically organized to cover advanced data structures topics from binary heaps to sorting to NP-completeness. Figures and examples illustrating successive stages of algorithms contribute to Weiss’ careful, rigorous and in-depth analysis of each type of algorithm.

  • 032144146XData Structures and Algorithm Analysis in C++, 3/E
    Weiss
    © 2007 | Addison-Wesley | Cloth | Instock
    ISBN-10: 032144146X | ISBN-13: 9780321441461
    Brief Description | Buy from myPearsonStore

Mark Allen Weiss is a Professor in the School of Computer Science at Florida International University. He received his Ph.D. in Computer Science from Princeton University where he studied under Robert Sedgewick. Dr.Weiss has received FIU's Excellence in Research Award, as well as the Teaching Incentive Program Award, which was established by the Florida Legislature to recognize teaching excellence. Mark Allen Weiss is on the Advanced Placement Computer Science Development Committee. He is the successful author of Algorithms, Data Structures, and Problem Solving with C++ and the series Data Structures and Algorithm Analysis in Pascal, Ada, C, and C++, with Addison-Wesley.



0201361221AB04062001

In this second edition of his successful book, experienced teacher and author Mark Allen Weiss continues to refine and enhance his innovative approach to algorithms and data structures. Written for the advanced data structures course, this text highlights theoretical topics such as abstract data types and the efficiency of algorithms, as well as performance and running time. Before covering algorithms and data structures, the author provides a brief introduction to C++ for programmers unfamiliar with the language. Dr. Weiss's clear writing style, logical organization of topics, and extensive use of figures and examples to demonstrate the successive stages of an algorithm make this an accessible, valuable text.

New to this Edition
  • An appendix on the Standard Template Library (STL)
  • C++ code, tested on multiple platforms, that conforms to the ANSI ISO final draft standard


0201361221B04062001

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