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This edition of Robert Sedgewick's popular work provides current and comprehensive coverage of important algorithms for Java programmers. Michael Schidlowsky and Sedgewick have developed new Java implementations that both express the methods in a concise and direct manner and provide programmers with the practical means to test them on real applications.
Many new algorithms are presented, and the explanations of each algorithm are much more detailed than in previous editions. A new text design and detailed, innovative figures, with accompanying commentary, greatly enhance the presentation. The third edition retains the successful blend of theory and practice that has made Sedgewick's work an invaluable resource for more than 400,000 programmers!
This particular book, Parts 1-4, represents the essential first half of Sedgewick's complete work. It provides extensive coverage of fundamental data structures and algorithms for sorting, searching, and related applications. Although the substance of the book applies to programming in any language, the implementations by Schidlowsky and Sedgewick also exploit the natural match between Java classes and abstract data type (ADT) implementations.
Whether you are learning the algorithms for the first time or wish to have up-to-date reference material that incorporates new programming styles with classic and new algorithms, you will find a wealth of useful information in this book.
I. FUNDAMENTALS.1. Introduction.
A Sample Problem: Connectivity.
Summary of Topics.2. Principles of Algorithm Analysis.
Implementation and Empirical Analysis.
Analysis of Algorithms.
Growth of Functions.
Examples of Algorithm Analysis.
Guarantees, Predictions, and Limitations.
II. DATA STRUCTURES.3. Elementary Data Structures.
Elementary List Processing.
Memory Allocation for Lists.
Compound Data Structures.4. Abstract Data Types.
Collections of Items.
Pushdown Stack ADT.
Examples of Stack ADT Clients.
Stack ADT Implementations.
Creation of a New ADT.
FIFO Queues and Generalized Queues.
Duplicate and Index Items.
Application-Based ADT Example.
Perspective.5. Recursion and Trees.
Divide and Conquer.
Mathematical Properties of Trees.
Recursive Binary-Tree Algorithms.
III. SORTING.6. Elementary Sorting Methods.
Rules of the Game.
Generic Sort Implementations.
Performance Characteristics of Elementary Sorts.
Sorting Linked Lists.
Key-Indexed Counting.7. Quicksort 315.
The Basic Algorithm.
Performance Characteristics of Quicksort.
Strings and Vectors.
Selection.8. Merging and Mergesort.
Abstract In-Place Merge.
Improvements to the Basic Algorithm.
Performance Characteristics of Mergesort.
Linked-List Implementations of Mergesort.
Recursion Revisited.9. Priority Queues and Heapsort.
Heap Data Structure.
Algorithms on Heaps.
Priority Queues for Index Items.
Binomial Queues.10. Radix Sorting.
Bits, Bytes, and Words.
MSD Radix Sort.
Three-Way Radix Quicksort.
LSD Radix Sort.
Performance Characteristics of Radix Sorts.
Sublinear-Time Sorts.11. Special-Purpose Sorts.
Batcher's Odd-Even Mergesort.
Sorting In Place.
IV. SEARCHING.12. Symbol Tables and BSTs.
Symbol-Table Abstract Data Type.
Index Implementations with Symbol Tables.
Binary Search Trees.
Performance Characteristics of BSTs.
Insertion at the Root in BSTs.
BST Implementations of Other ADT Functions.13. Balanced Trees.
Top-Down 2-3-4 Trees.
Performance Characteristics.14. Hashing.
Dynamic Hash Tables.
Perspective.15. Radix Search.
Digital Search Trees.
Multiway Tries and TSTs.
Text-String-Index Applications.16. External Searching.
Rules of the Game.
Indexed Sequential Access.