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Data Structures with C++ Using STL

ISBN-10: 0130858501
ISBN-13: 9780130858504
Edition: 2nd 2002
List price: $209.00
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Description: For CS2/Data Structures courses using C++. This book uses a modern object-oriented approach to data structures, unified around the notion of the Standard Template Library (STL) container classes. The book presents a systematic development of data  More...

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Book details

List price: $209.00
Edition: 2nd
Copyright year: 2002
Publisher: Prentice Hall PTR
Publication date: 7/17/2001
Binding: Hardcover
Pages: 1039
Size: 7.72" wide x 9.53" long x 1.73" tall
Weight: 4.884
Language: English

For CS2/Data Structures courses using C++. This book uses a modern object-oriented approach to data structures, unified around the notion of the Standard Template Library (STL) container classes. The book presents a systematic development of data structures supported by numerous examples and complete programs. The authors separate the applications of a data structure from its implementation. In the later chapters, the book transitions students into the study of applied algorithms. This creates a bridge to subsequent courses in advanced data structures and algorithms.

William Ford received his undergraduate education at MIT in applied mathematics and a Ph.D. in mathematics from the University of Illinois in 1972. His area of research was the numerical solution of partial differential equations, and the results of his work were published in three top-flight journals. After two years at Clemson University, he accepted an appointment at the University of the Pacific in Stockton, CA, where he taught mathematics and computer science. In 1986, he became a founding member of the Department of Computer Science that is now located in the School of Engineering and Computer Science. He served as Chair of the Department for eleven years and retired in 2014 as a recipient of the Order of Pacific, the highest award the University gives. Dr. Ford is the co-author of five computer science texts and two commercial software packages. For many years, he has taught computation for engineers, discrete mathematics, and computing theory. His interest in writing a book on numerical linear algebra arose from working with graduate engineering students. There is a tremendous need for engineers to be familiar with numerical linear algebra and its applications. Dr. Ford saw the need for the subject to be taught at the advanced undergraduate as well as the beginning graduate level. Yet, most engineering students have only applied linear algebra available to them, and books in the subject only touch on numerical aspects. The basics of linear algebra are necessary before a study of numerical linear algebra can begin, but few institutions can afford to offer two separate courses. As a result, he developed a book that in the early chapters provides the linear algebra necessary for a study of how to perform accurate computation in such problems such as solving general and specialized square linear systems, least-squares, computation of eigenvalues, and the iterative solution of large, sparse systems. The book contains many computational exercises and carefully chosen written exercises. Some of these written exercises introduce methods not directly covered in the text but, in each case, the method is developed in understandable parts. The same is true of proofs, and hints are provided for the most difficult problems.

(Most chapters end withChapter Summary, Classes and Libraries in the Chapter, Review Exercises, Written Exercises, Programming ExercisesandProgramming Projects.)
Preface
Introduction to Data Structures
What is this Book About?
Abstract View of Data Structures
An ADT as a Class
Implementing C++ Classes
Declaring and Using Objects
Implementing a Class with Inline Code
Application Programming Interface(API)
Strings
Object Design Techniques
Software Design
Handling Runtime Errors
Object Composition
Operator Overloading
Introduction to Algorithms
Selection Sort
Simple Search Algorithms
Analysis of Algorithms
Analyzing the Search Algorithms
Making Algorithms Generic
The Concept of Recursion
Problem Solving with Recursion
The Vector Container
Overview of STL Container Classes
Template Classes
The Vector Class
Vector Applications
Pointers and Dynamic Memory
C++ Pointers
Dynamic Memory
Classes Using Dynamic Memory
Assignment and Initialization
The Minivector Class
The Matrix Class
The List Container and Iterators
The List Container
Iterators
General List Insert And Erase Operations
Case Study: Graduation Lists
Stacks
The Stack ADT
Recursive Code and the Runtime Stack
Stack Implementation
Postfix Expressions. Case Study: Infix Expression Evaluation
Queues and Priority Queues
The Queue ADT
The Radix Sort
Implementing the Miniqueue Class
Case Study: Time-Driven Simulation
Array Based Queue Implementation
Priority Queues
Linked Lists
Linked List Nodes
Building Linked Lists
Handling The Back of the List
Implementing a Linked Queue
Doubly Linked Lists
Updating A Doubly Linked List
The Josephus Problem
The Minilist Class
Selecting a Sequence Container
Binary Trees
Tree Structures
Binary Tree Nodes
Binary Tree Scan Algorithms
Using Tree Scan Algorithms
Binary Search Trees
Using Binary Search Trees
Implementing the Stree Class
The Stree Iterator (Optional)
Associative Containers
Overview of Associative Containers
Sets
Maps
Multisets
Implementing Sets And Maps
Advanced Associative Structures
Hashing
Designing Hash Functions
Designing Hash Tables
The Hash Class
Hash Table Performance
2-3-4 Trees
Red-Black Trees
The Rbtree Class
Inheritance and Abstract Classes
Inheritance in C++
The Graphics Hierarchy
The Graphics System
Safe Vectors
Ordered Lists
Polymorphism and Virtual Functions
Abstract Classes
Heaps Binary Files and Bit Sets
Array Based Binary Trees
Heaps
Implementing a Priority Queue
Binary Files
Bitsets
Case Study: Huffman Compression
Recursive Algorithms
Divide and Conquer Algorithms
Combinatorics
Dynamic Programming
Backtracking: The Eight-Queens Problem
Graphs
Graph Terminology
The Graph Class
Graph Class Design
Graph Traversal Algorithms
Graph Traversal Applications
Graph Minimization Algorithms
Index

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