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parts1-4 Fundamentals, data structures, sorting, searching ISBN 9780201314526
内容説明
"This is an eminently readable book which an ordinary programmer, unskilled in mathematical analysis and wary of theoretical algorithms, ought to be able to pick up and get a lot out of.."
- Steve Summit, author of C Programming FAQs
Sedgewick has a real gift for explaining concepts in a way that makes them easy to understand. The use of real programs in page-size (or less) chunks that can be easily understood is a real plus. The figures, programs, and tables are a significant contribution to the learning experience of the reader; they make this book distinctive.
- William A. Ward, University of South Alabama
Robert Sedgewick has thoroughly rewritten and substantially expanded his popular work to provide current and comprehensive coverage of important algorithms and data structures. 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 250,000 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. The algorithms and data structures are expressed in concise implementations in C, so that you can both appreciate their fundamental properties and test them on real applications. Of course, the substance of the book applies to programming in any language.
Highlights
Expanded coverage of arrays, linked lists, strings, trees, and other basic data structures
Greater emphasis on abstract data types (ADTs) than in previous editions
Over 100 algorithms for sorting, selection, priority queue ADT implementations, and symbol table ADT (searching) implementations
New implementations of binomial queues, multiway radix sorting, Batcher's sorting networks, randomized BSTs, splay trees, skip lists, multiway tries, and much more
Increased quantitative information about the algorithms, including extensive empirical studies and basic analytic studies, giving you a basis for comparing them
Over 1000 new exercises to help you learn the properties of algorithms
Whether you are a student learning the algorithms for the first time or a professional interested in having up-to-date reference material, you will find a wealth of useful information in this book.
目次
I. FUNDAMENTALS.
Introduction.
Algorithms.
A Sample Problem -- Connectivity.
Union-Find Algorithms. Perspective.
Summary Of Topics.
Principles Of Algorithm Analysis.
Empirical Analysis.
Predictions And Guarantees.
Growth Of Functions.
Big-Oh Notation.
Example: Connectivity Algorithms.
Computational Complexity.
Perspective.
II. DATA STRUCTURES.
Elementary Data Structures.
Types And Structures.
Arrays.
Linked Lists.
Elementary List Processing.
Storage Allocation For Lists.
Strings.
Compound Structures.
Perspective.
Trees And Recursion.
Properties Of Trees.
Representing Binary Trees.
Representing Forests.
Traversing Trees.
Elementary Recursive Programs.
Divide-And-Conquer.
Depth-First Search.
Removing Recursion.
Elementary Abstract Data Types.
Pushdown Stack Adt.
Stack Adt Implementations.
Queue Adts And Implementations.
String Adt And Implementations.
Set Adt And Implementations.
Amortized Growth For Array Implementations.
III. SORTING.
Elementary Sorting Methods.
Rules Of The Game.
Selection Sort.
Insertion Sort.
Bubble Sort.
Performance Characteristics Of Elementary Sorts.
Shellsort.
Sorting Other Types Of Data.
Index And Pointer Sorting.
Sorting Linked Lists.
Distribution Counting.
Quicksort.
The Basic Algorithm.
Performance Characteristics Of Quicksort.
Stack Size.
Small Subfiles.
Median-Of-Three Partitioning.
Equal Keys.
Strings And Vectors.
Selection.
Mergesort.
Two-Way Merging.
Abstract Implace Merge.
Top-Down Mergesort.
Improvements To The Basic Algorithm.
Bottom-Up Mergesort.
Performance Characteristics Of Mergesort.
Linked-List Implementations Of Mergesort.
Recursion Revisited.
Priority Queues And Heapsort.
Elementary Implementations.
Heap Data Structure.
Algorithms On Heaps.
Heapsort.
Priority-Queue Abstract Data Type.
Indirect Priority Queues.
Binomial Queues.
Radix Sorting.
Bits, Bytes, And Words.
Binary Quicksort.
Msd Radix Sort.
Three-Way Radix Quicksort.
Lsd Radix Sort.
Performance Characteristics Of Radix Sorts.
Sublinear-Time Sorts.
Special-Purpose Sorts.
Batcher's Odd-Even Mergesort.
Sorting Networks.
External Sorting.
Sort-Merge Implementations.
Parallel Sort/Merge.
IV. SEARCHING.
Symbol Tables And Bsts.
Symbol-Table Abstract Data Type.
Key-Indexed Search.
Sequential Search.
Binary Search.
Binary Search Trees.
Performance Characteristics Of Bsts.
Index Implementations With Symbol Tables.
Insertion At The Root In Bsts.
Bst Implementations Of Other Adt Functions.
Balanced Trees.
Randomized Bsts.
Splay Bsts.
Top-Down 2-3-4 Trees.
Red-Black Trees.
Skip Lists.
Performance Characteristics.
Hashing.
Hash Functions.
Separate Chaining.
Linear Probing.
Double Hashing.
Dynamic Hash Tables.
Perspective.
Radix Searching.
Digital Search Trees.
Tries.
Patricia.
Multiway Tries And Tsts.
Text String Index Applications.
External Searching.
Indexed Sequential Access.
B-Trees.
Extendable Hashing.
Virtual Memory.
Program Index.
List Of Figures.
Index.
Epilogue. 0201314525T04062001
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part5 Graph algorithms ISBN 9780201316636
内容説明
Once again, Robert Sedgewick provides a current and comprehensive introduction to important algorithms. The focus this time is on graph algorithms, which are increasingly critical for a wide range of applications, such as network connectivity, circuit design, scheduling, transaction processing, and resource allocation. In this book, Sedgewick offers the same successful blend of theory and practice with concise implementations that can be tested on real applications, which has made his work popular with programmers for many years.
Algorithms in C, Third Edition, Part 5: Graph Algorithms is the second book in Sedgewick's thoroughly revised and rewritten series. The first book, Parts 1-4, addresses fundamental algorithms, data structures, sorting, and searching. A forthcoming third book will focus on strings, geometry, and a range of advanced algorithms. Each book's expanded coverage features new algorithms and implementations, enhanced descriptions and diagrams, and a wealth of new exercises for polishing skills. A focus on abstract data types makes the programs more broadly useful and relevant for the modern object-oriented programming environment.
Coverage includes:
A complete overview of graph properties and types
Diagraphs and DAGs
Minimum spanning trees
Shortest paths
Network flows
Diagrams, sample C code, and detailed algorithm descriptions
The Web site for this book (http://www.cs.princeton.edu/~rs/) provides additional source code for programmers along with numerous support materials for educators.
A landmark revision, Algorithms in C, Third Edition, Part 5 provides a complete tool set for programmers to implement, debug, and use graph algorithms across a wide range of computer applications.
目次
Preface.
Notes on Exercises.
17. Graph Properties and Types.
Glossary.
Graph ADT.
Adjacency-Matrix Representation.
Adjacency-Lists Representation.
Variations, Extensions, and Costs.
Graph Generators.
Simple, Euler, and Hamilton Paths.
Graph-Processing Problems.
18. Graph Search.
Exploring a Maze.
Depth-First Search.
Graph-Search ADT Functions.
Properties of DFS Forests.
DFS Algorithms.
Separability and Biconnectivity.
Breadth-First Search.
Generalized Graph Search.
Analysis of Graph Algorithms.
19. Digraphs and DAGs.
Glossary and Rules of the Game.
Anatomy of DFS in Digraphs.
Reachability and Transitive Closure.
Equivalence Relations and Partial Orders.
DAGs.
Topological Sorting.
Reachability in DAGs.
Strong Components in Digraphs.
Transitive Closure Revisited.
Perspective.
20. Minimum Spanning Trees.
Representations.
Underlying Principles of MST Algorithms.
Prim's Algorithm and Priority-First Search.
Kruskal's Algorithm.
Boruvka's Algorithm.
Comparisons and Improvements.
Euclidean MST.
21. Shortest Paths.
Underlying Principles.
Dijkstra's algorithm.
All-Pairs Shortest Paths.
Shortest Paths in Acyclic Networks.
Euclidean Networks.
Reduction.
Negative Weights.
Perspective.
22. Network Flows.
Flow Networks.
Augmenting-Path Maxflow Algorithms.
Preflow-Push Maxflow Algorithms.
Maxflow Reductions.
Mincost Flows.
Network Simplex Algorithm.
Mincost-Flow Reductions.
Perspective.
References for Part Five.
Index. 0201316633T09172001
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