This version of Sedgewick's bestselling book provides a comprehensive collection of algorithms implemented in C++. The algorithms included cover a broad range of fundamental and more advanced methods: sorting, searching, string processing, geometric, graph, and mathematical algorithms. Readers will discover-in an object-oriented programming environment-how key algorithms can be implemented, run, debugged, and used in real applications.
FUNDAMENTALS.
1. Introduction. Algorithms.
Outline of Topics.
2. C++ (AND C) Example: Euclid's Algorithm. Types of Data.
Input/Output.
Concluding Remarks
3. Elementary Data Structures. Arrays.
Linked Lists.
Storage Allocation.
Pushdown Stacks.
Queues.
Abstract and Concrete Data Types.
4. Trees. Glossary.
Properties.
Representing Binary Trees.
Representing Forests.
Traversing Trees.
5. Recursion. Recurrences.
Divide-and-Conquer.
Recursive Tree Traversal.
Removing Recursion.
Perspective.
6. Analysis of Algorithms. Selecting an Algorithm.
Empirical Analysis.
Program
Optimization.
Algorithms and Systems
SORTING ALGORITHMS.
7. Elementary Sorting Methods. Rules of the Game.
Selection Sort.
Insertion Sort.
Digression: Bubble Sort.
Performance Characteristics of Elementary Sorts.
Sorting Files with Large Records.
Shellsort.
Distribution Counting.
8. Quicksort. The Basic Algorithm.
Performance Characteristics of Quicksort.
Removing Recursion.
Small Subfiles.
Median-of-Three Partitioning.
Selection.
9. Radix Sorting. Bits.
Radix Exchange Sort.
Straight Radix Sort.
Performance Characteristics of Radix Sorts.
A Linear Sort.
10. Priority Queues. Elementary Implementations.
Heap Data Structure.
Algorithms on Heaps.
Heapsort.
Indirect Heaps.
Advanced Implementations
11. Mergesort. Merging.
Mergesort.
Lit Mergesort.
Bottom-Up Mergesort.
Performance Characteristics.
Optimized Implementations.
Recursion Revisited.
12. External Sorting. Sort-Merge.
Balanced Multiway Merging.
Replacement
Selection.
Practical Considerations.
Polyphase Merging.
An Easier Way
SEARCHING ALGORITHMS.
13. Elementary Searching Methods. Sequential Searching Methods.
Binary Search.
Binary Tree Search.
Deletion.
Indirect Binary Search Trees.
14. Balanced Trees. Top-Down 2-3-4 Trees.
Red-Black Trees.
Other Algorithms.
15. Hashing. Hash Functions.
Separate Chaining.
Linear Probing.
Double Hashing.
Perspective
16. Radix Searching. Digital Search Trees.
Radix Search Tries.
Multiway Radix Searching.
Patricia.
17. External Searching. Indexed Sequential Access.
B-Trees.
Extendible Hashing.
Virtual Memory.
STRING PROCESSING.
18. String Searching. A Short History.
Brute-Force Algorithm.
Knuth-Morris-Pratt Algorithm.
Boyer-Moore Algorithm.
Rabin-Karp Algorithm.
Multiple Searches.
19. Pattern Matching. Describing Patterns.
Pattern Matching Machines.
Representing the Machine.
Simulating the Machine.
20. Parsing. Context-Free Grammars.
Top-Down Parsing.
Bottom-Up Parsing.
Compilers.
Compiler-Compilers.
21. File Compression. Run-Length Encoding.
Variable-Length Encoding.
Building the Huffman Code.
Implementation.
22. Cryptology. Rules of the Game.
Simple Methods.
Encryption/Decryption Machines.
Public-Key Cryptosystems.
GEOMETRIC ALGORITHMS.
23. Elementary Geometric Methods. Points, Lines, and Polygons.
Line Segment Intersection.
Simple Closed Path.
Inclusion in a Polygon.
Perspective.
24. Finding the Convex Hull. Rules of the Game.
Package-Wrapping.
The Graham Scan.
Interior Elimination.
Performance Issues.
25. Range Searching. Elementary Methods.
Grid Method.
Two-Dimensional Trees.
Multidimensional Range Searching.
26. Geometric Intersection. Horizontal and Vertical Lines.
Implementation.
General Line Intersection.
27. Closest-Point Problems. Closest-Pair Problem.
Voronoi Diagrams.
GRAPH ALGORITHMS.
28. Elementary Graph Algorithms. Glossary.
Representation.
Depth-First Search.
Nonrecursive Depth-First Search.
Breadth-First Search.
Mazes.
Perspective.
29. Connectivity. Connected Components.
Biconnectivity.
Union-Find Connectivity.
30. Weighted Graphs. Minimum Spanning Tree.
Priority-First Search.
Kruskal's Method.
Shortest Path.
Minimum Spanning Tree and Shortest Paths in Dense Graphs.
Geometric Problems.
31. Directed Graphs. Depth-First Search.
Transitive Closure.
All Shortest Paths.
Topological Sorting.
Strongly Connected Components.
32. Network Flow. The Network Flow Problem.
Ford-Fulkerson Method.
Network Searching.
33. Matching. Bipartite Graphs.
Stable Marriage Problems.
Advanced Algorithms.
MATHEMATICAL ALGORITHMS.
34. Random Numbers. Applications.
Linear Congruential Method.
Additive Congruential Method.
Testing Randomness.
Implementational Notes.
35. Arithmetic. Polynomial Arithmetic.
Polynomial Evaluation and Interpolation.
Polynomial Multiplication.
Arithmetic Operations with Large Integers.
Matrix Arithmetic.
36. Gaussian Elimination. A Simple Example.
Outline of the Method.
Variations and Extensions.
37. Curve Fittings. Polynomial Interpolation.
Spline Interpolation.
Method of Least Squares.
38. Integration. Symbolic Integration.
Simple Quadrature Methods.
Compound Methods.
Adaptive Quadrature.
ADVANCED TOPICS.
39. Parallel Algorithms. General Approaches.
Perfect Shuffles.
Systolic Arrays.
Perspective.
40. The Fast Fourier Transform. Evaluate, Multiply, Interpolate.
Complex Roots of Unity.
Evaluation at the Roots of Unity.
Interpolation at the Roots of Unity.
Implementation.
41. Dynamic Programming. Knapsack Problem.
Matrix Chain Product.
Optimal Binary Search Trees.
Time and Space Requirements.
42. Linear Programming. Linear Programs.
Geometric Interpretation.
The Simplex Method.
Implementation.
43. Exhaustive Search. Exhaustive Search in Graphs.
Backtracking.
Digression: Permutation Generation.
Approximation Algorithms.
44. NP-Complete Problems. Deterministic and Nondeterministic Polynomial-Time Algorithms.
NP-Completeness.
Cook's Theorem.
Some NP-Complete Problems. 0201510596T04062001
CS0701:
Algorithms
Robert Sedgewick is the William O. Baker Professor of Computer Science at Princeton University. He is a Director of Adobe Systems and has served on the research staffs at Xerox PARC, IDA, and INRIA. He earned his Ph.D from Stanford University under Donald E. Knuth.
0201510596AB06262002
The latest addition to Robert Sedgewick's popular series of bookscarries his comprehensive collection of algorithms into anobject-oriented programming (OOP) environment with implementationin the C++ programming language. These algorithms cover a broadrange of fundamental and more advanced methods: sorting,searching, string-processing, geometric, graph, and mathematicalalgorithms. The algorithms are all expressed in terms of conciseimplementations in C++, so that readers can both appreciate theirbasic properties and test them on real applications.
The treatment of analysis of algorithsm is carefully developed. When appropriate, analytic results are discussed to illustratewhy certain algorithms are prefered, and in some cases, therelationship of the proactical algorithms being discussed topurely theoretical results is also described.
The ultimate aim of the book is to improve programming practice,whatever the environment, whatever the implementation language. Sedgweick describes the basic methods to be considered in everycase.
Features- Hundreds of detailed, innovative figures clearly demonstratehow important algorithms work.
- Throughout the book, "properties" sections encapsulatespecific information on the performance characteristics ofalgorithms.
- Six chapters discuss fundamental concepts, including a briefintroduction to data structures.
Algorithms in C++ provides readers with the tools to implement,run, and debug useful algorithms with confidence. This book is ahelpful guide for users engaged in the transition to orexperimentation with OOP and/or the C++ language. It may be usedfor self study, or as a reference for developers or computersystems or applications programs.
0201510596B04062001
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