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The latest addition to Robert Sedgewick's popular series of books carries his comprehensive collection of algorithms into an object-oriented programming (OOP) environment with implementation in the C++ programming language. These algorithms cover a broad range of fundamental and more advanced methods: sorting, searching, string-processing, geometric, graph, and mathematical algorithms. The algorithms are all expressed in terms of concise implementations in C++, so that readers can both appreciate their basic properties and test them on real applications.
The treatment of analysis of algorithsm is carefully developed. When appropriate, analytic results are discussed to illustrate why certain algorithms are prefered, and in some cases, the relationship of the proactical algorithms being discussed to purely 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 every case.
Features :
Algorithms in C++ provides readers with the tools to implement, run, and debug useful algorithms with confidence. This book is a helpful guide for users engaged in the transition to or experimentation with OOP and/or the C++ language. It may be used for self study, or as a reference for developers or computer systems or applications programs.
Author Bio
Sedgewick, Robert : Princeton University
Robert Sedgewick is the William O. Baker Professor of Computer Science at Princeton University and has held visiting research positions at INRIA, the Institute for Defense Analyses, and Xerox PARC. He is the author of a widely used series of books on algorithms.
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.
The latest addition to Robert Sedgewick's popular series of books carries his comprehensive collection of algorithms into an object-oriented programming (OOP) environment with implementation in the C++ programming language. These algorithms cover a broad range of fundamental and more advanced methods: sorting, searching, string-processing, geometric, graph, and mathematical algorithms. The algorithms are all expressed in terms of concise implementations in C++, so that readers can both appreciate their basic properties and test them on real applications.
The treatment of analysis of algorithsm is carefully developed. When appropriate, analytic results are discussed to illustrate why certain algorithms are prefered, and in some cases, the relationship of the proactical algorithms being discussed to purely 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 every case.
Features :
Algorithms in C++ provides readers with the tools to implement, run, and debug useful algorithms with confidence. This book is a helpful guide for users engaged in the transition to or experimentation with OOP and/or the C++ language. It may be used for self study, or as a reference for developers or computer systems or applications programs.
Author Bio
Sedgewick, Robert : Princeton University
Robert Sedgewick is the William O. Baker Professor of Computer Science at Princeton University and has held visiting research positions at INRIA, the Institute for Defense Analyses, and Xerox PARC. He is the author of a widely used series of books on algorithms.
Table of Contents
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.