Monographs in Computer Science
cover

Abstraction, Refinement and Proof for Probabilistic Systems

Authors: McIver, Annabelle, Morgan, Charles Carroll

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About this book

Probabilistic techniques are increasingly being employed in computer programs and systems because they can increase efficiency in sequential algorithms, enable otherwise nonfunctional distribution applications, and allow quantification of risk and safety in general. This makes operational models of how they work, and logics for reasoning about them, extremely important.

Abstraction, Refinement and Proof for Probabilistic Systems presents a rigorous approach to modeling and reasoning about computer systems that incorporate probability. Its foundations lie in traditional Boolean sequential-program logic—but its extension to numeric rather than merely true-or-false judgments takes it much further, into areas such as randomized algorithms, fault tolerance, and, in distributed systems, almost-certain symmetry breaking. The presentation begins with the familiar "assertional" style of program development and continues with increasing specialization: Part I treats probabilistic program logic, including many examples and case studies; Part II sets out the detailed semantics; and Part III applies the approach to advanced material on temporal calculi and two-player games.

Topics and features:

* Presents a general semantics for both probability and demonic nondeterminism, including abstraction and data refinement

* Introduces readers to the latest mathematical research in rigorous formalization of randomized (probabilistic) algorithms * Illustrates by example the steps necessary for building a conceptual model of probabilistic programming "paradigm"

* Considers results of a large and integrated research exercise (10 years and continuing) in the leading-edge area of "quantitative" program logics

* Includes helpful chapter-ending summaries, a comprehensive index, and an appendix that explores alternative approaches

This accessible, focused monograph, written by international authorities on probabilistic programming, develops an essential foundation topic for modern programming and systems development. Researchers, computer scientists, and advanced undergraduates and graduates studying programming or probabilistic systems will find the work an authoritative and essential resource text.

Table of contents (11 chapters)

Table of contents (11 chapters)
  • Introduction to pGCL: Its logic and its model

    Pages 3-36

  • Probabilistic loops: Invariants and variants

    Pages 37-78

  • Case studies in termination: Choice coordination, the dining philosophers, and the random walk

    Pages 79-106

  • Probabilistic data refinement: The steam boiler

    Pages 107-125

  • Theory for the demonic model

    Pages 129-164

Buy this book

eBook $149.00
price for USA in USD
  • ISBN 978-0-387-27006-7
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $199.99
price for USA in USD
  • ISBN 978-0-387-40115-7
  • Free shipping for individuals worldwide
  • Institutional customers should get in touch with their account manager
  • Covid-19 shipping restrictions & severe weather in the US may cause delays
  • Usually ready to be dispatched within 3 to 5 business days, if in stock
Softcover $199.00
price for USA in USD
  • ISBN 978-1-4419-2312-7
  • Free shipping for individuals worldwide
  • Institutional customers should get in touch with their account manager
  • Covid-19 shipping restrictions & severe weather in the US may cause delays
  • Usually ready to be dispatched within 3 to 5 business days, if in stock
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Bibliographic Information

Bibliographic Information
Book Title
Abstraction, Refinement and Proof for Probabilistic Systems
Authors
Series Title
Monographs in Computer Science
Copyright
2005
Publisher
Springer-Verlag New York
Copyright Holder
Springer-Verlag New York
eBook ISBN
978-0-387-27006-7
DOI
10.1007/b138392
Hardcover ISBN
978-0-387-40115-7
Softcover ISBN
978-1-4419-2312-7
Series ISSN
0172-603X
Edition Number
1
Number of Pages
XX, 388
Number of Illustrations
63 b/w illustrations
Topics