Free download Algorithm Design and Applications in PDF written by Michael T. Goodrich (University of California), Roberto Tamassia (Department of Computer Science Brown University) and published by John Wiley & Sons, Inc.
According to the Authors, “This book is designed to provide a comprehensive introduction to the design and analysis of computer algorithms and data structures. We have made each chapter to be relatively independent of other chapters so as to provide instructors and readers greater flexibility with respect to which chapters to explore. Moreover, the extensive collection of topics we include provides coverage of both classic and emerging algorithmic methods, including the following:
- Mathematics for asymptotic analysis, including amortization and randomization
- General algorithm design techniques, including the greedy method, divide and-conquer, and dynamic programming
- Data structures, including lists, trees, heaps, search trees, B-trees, hash tables, skip lists, union-find structures, and multidimensional trees
- Algorithmic frameworks, including NP-completeness, approximation algorithms, and external-memory algorithms
- Fundamental algorithms, including sorting ,graph algorithms, computational geometry, numerical algorithms,cryptography,Fast Fourier Transform(FFT), and linear programming.
This is an exciting time for computer science. Computers have moved beyond their early uses as computational engines to now be used as information processors, with applications to every other discipline. Moreover, the expansion of the Internet has brought about new paradigms and modalities for computer applications to society and commerce. For instance, computers can be used to store and retrieve large amounts of data, and they are used in many other application areas, such as sports, video games, biology, medicine, social networking, engineering, and science. Thus, we feel that algorithms should be taught to emphasize not only their mathematical analysis but also their practical applications. To fulfill this need, we have written each chapter to begin with a brief discussion of an application that motivates the topic of that chapter. In some cases, this application comes from areal-world use of the topic discussed in the chapter,and in other cases it is a contrived application that highlights how the topic of the chapter could be used in practice. Our intent in providing this motivation is to give readers a conceptual context and practical justification to accompany their reading of each chapter. In addition to this application-based motivation we include also detailed pseudo code descriptions and complete mathematical analysis. Indeed, we feel that mathematical rigor should not simply be for its own sake,but also for its pragmatic implications.
This book is structured to allow an instructor a great deal of freedom in how to organize and present material. The dependence between chapters is relatively minimal, which allows the instructor to cover topics in her preferred sequence. Moreover, each chapter is designed so that it can be covered in 1–3 lectures,depending on the depth of coverage.
Table of Content
- Algorithm Analysis
- Basic Data Structures
- Binary Search Trees
- Balanced Binary Search Trees
- Priority Queues and Heaps
- Hash Tables
- Union-Find Structures
- Merge Sort and Quick Sort
- Fast Sorting and Selection
- The Greedy Method
- Divide and Conquer
- Dynamic Programming
- Graphs and Traversals
- Shortest Paths
- Minimum Spanning Trees
- Network Flow and Matching
- NP-Completeness
- Approximation Algorithms
- Randomized Algorithms
- B-Trees and External Memory
- Multi-Dimensional Searching
- Computational Geometry
- String Algorithms
- Cryptography
- The Fast Fourier Transform
- Linear Programming
- Bibliography
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