Programmer's companion to algorithm analysis / by Ernst L. Leiss

By: Leiss, Ernst LMaterial type: Text

TextLanguage: English Publication details: Boca Raton: Chapman & Hall/CRC, 2007 Description: 255pISBN: 9781584886730Subject(s): Programming (Mathematics) | Algorithms -- Data processingDDC classification: 004.421

Contents:

PART 1 THE ALGORITHM SIDE: REGULARITY, PREDICTABILITY, AND ASYMPTOTICS A Taxonomy of Algorithmic Complexity Fundamental Assumptions Underlying Algorithmic Complexity Examples of Complexity Analysis PART 2 THE SOFTWARE SIDE: DISAPPOINTMENTS AND HOW TO AVOID THEM Sources of Disappointments Implications of Nonuniform Memory for Software Implications of Compiler and Systems Issues for Software Implicit Assumptions Implications of the Finiteness of the Representation of Numbers Asymptotic Complexities and the Selection of Algorithms Infeasibility and Undecidability: Implications for Software Development PART 3 CONCLUSION Appendix I: Algorithms Every Programmer Should Know Appendix II: Overview of Systems Implicated in Program Analysis Appendix III: NP-Completeness and Higher Complexity Classes Appendix IV: Review of Undecidability BIBLIOGRAPHY INDEX

Summary: Until now, no other book examined the gap between the theory of algorithms and the production of software programs. Focusing on practical issues, A Programmer's Companion to Algorithm Analysis carefully details the transition from the design and analysis of an algorithm to the resulting software program. Consisting of two main complementary parts, the book emphasizes the concrete aspects of translating an algorithm into software that should perform based on what the algorithm analysis indicated. In the first part, the author describes the idealized universe that algorithm designers inhabit while the second part outlines how this ideal can be adapted to the real world of programming. The book explores analysis techniques, including crossover points, the influence of the memory hierarchy, implications of programming language aspects, such as recursion, and problems arising from excessively high computational complexities of solution methods. It concludes with four appendices that discuss basic algorithms; memory hierarchy, virtual memory management, optimizing compilers, and garbage collection; NP-completeness and higher complexity classes; and undecidability in practical terms. Applying the theory of algorithms to the production of software, A Programmer's Companion to Algorithm Analysis fulfills the needs of software programmers and developers as well as students by showing that with the correct algorithm, you can achieve a functional software program.

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Includes bibliography, and index.

PART 1 THE ALGORITHM SIDE: REGULARITY, PREDICTABILITY, AND ASYMPTOTICS
A Taxonomy of Algorithmic Complexity
Fundamental Assumptions Underlying Algorithmic Complexity
Examples of Complexity Analysis
PART 2 THE SOFTWARE SIDE: DISAPPOINTMENTS AND HOW TO AVOID THEM
Sources of Disappointments
Implications of Nonuniform Memory for Software
Implications of Compiler and Systems Issues for Software
Implicit Assumptions
Implications of the Finiteness of the Representation of Numbers
Asymptotic Complexities and the Selection of Algorithms
Infeasibility and Undecidability: Implications for Software Development
PART 3 CONCLUSION
Appendix I: Algorithms Every Programmer Should Know
Appendix II: Overview of Systems Implicated in Program Analysis
Appendix III: NP-Completeness and Higher Complexity Classes
Appendix IV: Review of Undecidability
BIBLIOGRAPHY
INDEX

Until now, no other book examined the gap between the theory of algorithms and the production of software programs. Focusing on practical issues, A Programmer's Companion to Algorithm Analysis carefully details the transition from the design and analysis of an algorithm to the resulting software program.

Consisting of two main complementary parts, the book emphasizes the concrete aspects of translating an algorithm into software that should perform based on what the algorithm analysis indicated. In the first part, the author describes the idealized universe that algorithm designers inhabit while the second part outlines how this ideal can be adapted to the real world of programming. The book explores analysis techniques, including crossover points, the influence of the memory hierarchy, implications of programming language aspects, such as recursion, and problems arising from excessively high computational complexities of solution methods. It concludes with four appendices that discuss basic algorithms; memory hierarchy, virtual memory management, optimizing compilers, and garbage collection; NP-completeness and higher complexity classes; and undecidability in practical terms.

Applying the theory of algorithms to the production of software, A Programmer's Companion to Algorithm Analysis fulfills the needs of software programmers and developers as well as students by showing that with the correct algorithm, you can achieve a functional software program.

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