Data Structures and Algorithms in Java, 5th Edition
ISBN: 9780470383261 | 0470383267
Edition: 5thFormat: Hardcover
Publisher: Wiley
Pub. Date: 2/1/2010
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This newest edition examines fundamental data structures by following a consistent object-oriented framework that builds intuition and analysis skills of data structures and algorithms Presents new figures, simpler language, and more practical motivations from real-world scenarios Numerous illustrations, Web-based animations, and simplified mathematical analyses help readers quickly learn important concepts
| Java Primer | |
| Getting Started: Classes, Types, and Objects | |
| Methods | |
| Expressions | |
| Control Flow | |
| Arrays | |
| Simple Input and Output | |
| An Example Program | |
| Nested Classes and Packages | |
| Writing a Java Program | |
| Exercises | |
| Object-Oriented Design | |
| ... MORE | |
| Inheritance and Polymorphism | |
| Exceptions | |
| Interfaces and Abstract Classes | |
| Casting and Generics | |
| Exercises | |
| Indices, Nodes, and Recursion | |
| Using Arrays | |
| Singly Linked Lists | |
| Doubly Linked Lists | |
| Circularly Linked Lists and Linked-List Sorting | |
| Recursion | |
| Exercises | |
| Analysis Tools | |
| The Seven Functions Used in This Book | |
| Analysis of Algorithms | |
| Simple Justification Techniques | |
| Exercises | |
| Stacks, Queues, and Deques | |
| Stacks | |
| Queues | |
| Double-Ended Queues | |
| Exercises | |
| List and Iterator ADTs | |
| Array Lists | |
| Node Lists | |
| Iterators | |
| List ADTs and the Collections Framework | |
| Case Study: The Move-to-Front Heuristic | |
| Exercises | |
| Trees | |
| General Trees | |
| Tree Traversal Algorithms | |
| Binary Trees | |
| Exercises | |
| Heaps and Priority Queues | |
| The Priority Queue Abstract Data Type | |
| Implementing a Priority Queue with a List | |
| Heaps | |
| Adaptable Priority Queues | |
| Exercises | |
| Hash Tables, Maps, and Skip Lists | |
| Maps | |
| Hash Tables | |
| Ordered Maps | |
| Skip Lists | |
| Dictionaries | |
| Exercises | |
| Search Trees | |
| Binary Search Trees | |
| AVL Trees | |
| Splay Trees | |
| (2,4) Trees | |
| Red-Black Trees | |
| Exercises | |
| Sorting, Sets, and Selection | |
| Merge-Sort | |
| Quick-Sort | |
| Studying Sorting through an Algorithmic Lens | |
| Sets and Union/Find Structures | |
| Selection | |
| Exercises | |
| Strings and Dynamic Programming | |
| String Operations | |
| Dynamic Programming | |
| Pattern Matching Algorithms | |
| Text Compression and the Greedy Method | |
| Tries | |
| Exercises | |
| Graph Algorithms | |
| Graphs | |
| Data Structures for Graphs | |
| Graph Traversals | |
| Directed Graphs | |
| Shortest Paths | |
| Minimum Spanning Trees | |
| Exercises | |
| Memory Management and B-Trees | |
| Memory Management | |
| External Memory and Caching | |
| External Searching and B-Trees | |
| External-Memory Sorting | |
| Exercises | |
| A Useful Mathematical Facts | |
| Bibliography | |
| Index | |
| Table of Contents provided by Publisher. All Rights Reserved. |
Professors Goodrich and Tamassia are well-recognized researchers in data structures and algorithms. Michael Goodrich received his Ph.D. in Computer Science from Purdue University. He is currently a professor in the Department of Computer Science at the University of California, Irvine. Roberto Tamassia received his Ph.D. in Electrical and Computer Engineering from the University of Illinois at Urbana-Champaign. He is currently a professor in the Department Science at Brown University. Both professors are winners of numerous teaching awards for their teaching of data structures and algorithms.
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