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Introduction to the Design and Analysis of Algorithms

by

Introduction to the Design and Analysis of Algorithms Cover

 

Synopses & Reviews

Publisher Comments:

Algorithms

 

Introduction to The Design & Analysis of Algorithms, 2nd Edition

Anany Levitin, Villanova University

 

Valued by students and trusted by instructors, Introduction to the Design and Analysis of Algorithms employs a comprehensive taxonomy of algorithm design techniques that is more powerful and intuitive than the traditional approach.

 

It provides a coherent and pedagogically sound framework for learning and teaching algorithms. An extensive, detailed solutions manual is available online for the benefit of students and instructors. Student learning is further supported by exercise hints and chapter summaries. Popular puzzles and games provide motivation for students, and rhetorical questioning serves as an effective learning device.

 

Ideal for a basic course in the design and analysis of algorithms, this Second Edition features 80 new puzzles and exercises, as well as:

• Separate sections on the analysis of nonrecursive and recursive algorithms

• Coverage of empirical analysis and algorithm visualization

• Revised section on approximation algorithms• Brand-new chapter on iterative improvement algorithms covering the simplex method, network flows, maximum matching in bipartite graphs, and the stable marriage problem

Synopsis:

Based on a new classification of algorithm design techniques and a clear delineation of analysis methods, Introduction to the Design and Analysis of Algorithms, 2e presents the subject in a truly innovative manner.  Written in a reader-friendly style, the book encourages broad problem-solving skills while thoroughly covering the material required for introductory algorithms. The author emphasizes conceptual understanding before the introduction of the formal treatment of each technique. Popular puzzles are used to motivate readers' interest and strengthen their skills in algorithmic problem solving. Other enhancement features include chapter summaries, hints to the exercises, and a solution manual. For those interested in learning more about algorithms.

Table of Contents

Contents

 

Preface

1Introduction

1.1 What is an Algorithm?

1.2 Fundamentals of Algorithmic Problem Solving

1.3 Important Problem Types

1.4 Fundamental Data Structures

 

2 Fundamentals of the Analysis of Algorithm Efficiency

2.1 Analysis Framework

2.2 Asymptotic Notations and Basic Efficiency Classes

2.3 Mathematical Analysis of Nonrecursive Algorithms

2.4 Mathematical Analysis of Recursive Algorithms

2.5 Example: Fibonacci Numbers

2.6 Empirical Analysis of Algorithms

2.7 Algorithm Visualization

 

3 Brute Force

3.1 Selection Sort and Bubble Sort

3.2 Sequential Search and Brute-Force String Matching

3.3 Closest-Pair and Convex-Hull Problems by Brute Force

3.4 Exhaustive Search

 

4 Divide-and-Conquer

4.1 Mergesort

4.2 Quicksort

4.3 Binary Search

4.4 Binary Tree Traversals and Related Properties

4.5 Multiplication of Large Integers and Strassen’s Matrix Multiplication

4.6 Closest-Pair and Convex-Hull Problems by Divide-and-Conquer

 

5 Decrease-and-Conquer

5.1 Insertion Sort

5.2 Depth-First Search and Breadth-First Search

5.3 Topological Sorting

5.4 Algorithms for Generating Combinatorial Objects

5.5 Decrease-by-a-Constant-Factor Algorithms

5.6 Variable-Size-Decrease Algorithms

 

6 Transform-and-Conquer

6.1 Presorting

6.2 Gaussian Elimination

6.3 Balanced Search Trees

6.4 Heaps and Heapsort

6.5 Horner’s Rule and Binary Exponentiation

6.6 Problem Reduction

 

7 Space and Time Tradeoffs

7.1 Sorting by Counting

7.2 Input Enhancement in String Matching

7.3 Hashing

7.4 B-Trees

 

8 Dynamic Programming

8.1 Computing a Binomial Coefficient

8.2 Warshall’s and Floyd’s Algorithms

8.3 Optimal Binary Search Trees

8.4 The Knapsack Problem and Memory Functions

 

9 Greedy Technique

9.1 Prim’s Algorithm

9.2 Kruskal’s Algorithm

9.3 Dijkstra’s Algorithm

9.4 Huffman Trees

 

10 Iterative Improvement

10.1 The Simplex Method

10.2 The Maximum-Flow Problem

10.3 Maximum Matching in Bipartite Graphs

10.4 The Stable Marriage Problem

 

11 Limitations of Algorithm Power

11.1 Lower-Bound Arguments

11.2 Decision Trees

11.3 P, NP, and NP-complete Problems

11.4 Challenges of Numerical Algorithms 4

 

12 Coping with the Limitations of Algorithm Power

12.1 Backtracking

12.2 Branch-and-Bound

12.3 Approximation Algorithms for NP-hard Problems

12.4 Algorithms for Solving Nonlinear Equations

 

Epilogue

 

APPENDIX A

Useful Formulas for the Analysis of Algorithms

 

APPENDIX B

Short Tutorial on Recurrence Relations

 

Bibliography

 

Hints to Exercises

 

Index

Product Details

ISBN:
9780321358288
Publisher:
Academic Internet Publishers
Subject:
Computer algorithms
Author:
Levitin, Anany V.
Author:
Levitin, Anany
Author:
Cram101 Textbook Reviews
Subject:
Programming - Algorithms
Subject:
Software Engineering-Algorithms
Subject:
Education-General
Copyright:
Edition Number:
2
Edition Description:
Trade paper
Publication Date:
February 2006
Binding:
TRADE PAPER
Grade Level:
College/higher education:
Language:
English
Illustrations:
Y
Pages:
592
Dimensions:
9.31x7.50x.87 in. 1.96 lbs.

Related Subjects


Computers and Internet » Computers Reference » General
Computers and Internet » Software Engineering » Algorithms
Computers and Internet » Software Engineering » General
Textbooks » General

Introduction to the Design and Analysis of Algorithms
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$ In Stock
Product details 592 pages Addison Wesley Publishing Company - English 9780321358288 Reviews:
"Synopsis" by , Based on a new classification of algorithm design techniques and a clear delineation of analysis methods, Introduction to the Design and Analysis of Algorithms, 2e presents the subject in a truly innovative manner.  Written in a reader-friendly style, the book encourages broad problem-solving skills while thoroughly covering the material required for introductory algorithms. The author emphasizes conceptual understanding before the introduction of the formal treatment of each technique. Popular puzzles are used to motivate readers' interest and strengthen their skills in algorithmic problem solving. Other enhancement features include chapter summaries, hints to the exercises, and a solution manual. For those interested in learning more about algorithms.
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