Data Structures and Algorithms with Object Oriented Design Patterns in Java
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More About This Title Data Structures and Algorithms with Object Oriented Design Patterns in Java
English
Create sound software designs with data structures that use modern object-oriented design patterns! Author Bruno Preiss presents the fundamentals of data structures and algorithms from a modern, object-oriented perspective. The text promotes object-oriented design using Java and illustrates the use of the latest object-oriented design patterns. Virtually all the data structures are discussed in the context of a single class hierarchy. This framework clearly shows the relationships between data structures and illustrates how polymorphism and inheritance can be used effectively. Key Features of the Text
* All data structures are presented using a common framework. This shows the relationship between the data structures and how they are implemented.
* Object-oriented design patterns are used to demonstrate how a good design fits together and transcends the problem at hand.
* A single Java software design is used throughout the text to provide a better understanding of the operation of complicated data structures.
* Just-in-time presentation of mathematical analysis techniques introduces students to mathematical concepts as needed.
Visit the Text's Web Site A comprehensive web site is available for users of the text at www.wiley.com/college/preiss. The site includes:
* The Web Book (a hypertext version of the complete book)
* Links to the Java Source Code (all the program examples from the text)
* Opus5 Package (a Java package comprised of all the source code from the text)
* Documentation (source code documentation)
* Demo Applets (various Java applets that illustrate data structures and algorithms from the text)
* Archive (JAR format archive of the source code from the text)
* Front Matter (table of contents and preface)
* Solutions Manual (password required)
* Errata
* All data structures are presented using a common framework. This shows the relationship between the data structures and how they are implemented.
* Object-oriented design patterns are used to demonstrate how a good design fits together and transcends the problem at hand.
* A single Java software design is used throughout the text to provide a better understanding of the operation of complicated data structures.
* Just-in-time presentation of mathematical analysis techniques introduces students to mathematical concepts as needed.
Visit the Text's Web Site A comprehensive web site is available for users of the text at www.wiley.com/college/preiss. The site includes:
* The Web Book (a hypertext version of the complete book)
* Links to the Java Source Code (all the program examples from the text)
* Opus5 Package (a Java package comprised of all the source code from the text)
* Documentation (source code documentation)
* Demo Applets (various Java applets that illustrate data structures and algorithms from the text)
* Archive (JAR format archive of the source code from the text)
* Front Matter (table of contents and preface)
* Solutions Manual (password required)
* Errata
English
Bruno R. Preiss is an Associate Professor in the Department of Electrical and Computer Engineering at the University of Waterloo, Canada. He is a member of the Parallel and Distributed Systems Group, the Computer Communications Networks Group, and the VLSI Research Group. After earning a B.A.Sc. degree in Engineering Science, Professor Preiss received an M.A.Sc. and Ph.D. in Electrical Engineering from the University of Toronto, Canada.
English
Algorithm Analysis.
Asymptotic Notation.
Foundational Data Structures.
Data Types and Abstraction.
Stacks, Queues, and Deques.
Ordered Lists and Sorted Lists.
Hashing, Hash Tables, and Scatter Tables.
Trees.
Search Trees.
Heaps and Priority Queues.
Sets, Multisets, and Partitions.
Garbage Collection.
Algorithmic Patterns and Problem Solvers.
Sorting Algorithms and Sorters.
Graphs and Graph Algorithms.
Appendices.
Bibliography.
Index.
Asymptotic Notation.
Foundational Data Structures.
Data Types and Abstraction.
Stacks, Queues, and Deques.
Ordered Lists and Sorted Lists.
Hashing, Hash Tables, and Scatter Tables.
Trees.
Search Trees.
Heaps and Priority Queues.
Sets, Multisets, and Partitions.
Garbage Collection.
Algorithmic Patterns and Problem Solvers.
Sorting Algorithms and Sorters.
Graphs and Graph Algorithms.
Appendices.
Bibliography.
Index.
