Abstraction, Refinement and Proof for Probabilistic Systems

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...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριοι συγγραφείς: McIver, Annabelle (Συγγραφέας), Morgan, Carroll (Συγγραφέας)
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: New York, NY : Springer New York, 2005.
Σειρά:Monographs in Computer Science,
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
LEADER 04931nam a22005775i 4500
001 978-0-387-27006-7
003 DE-He213
005 20151204154613.0
007 cr nn 008mamaa
008 100301s2005 xxu| s |||| 0|eng d
020 |a 9780387270067  |9 978-0-387-27006-7 
024 7 |a 10.1007/b138392  |2 doi 
040 |d GrThAP 
050 4 |a QA76.758 
072 7 |a UMZ  |2 bicssc 
072 7 |a UL  |2 bicssc 
072 7 |a COM051230  |2 bisacsh 
082 0 4 |a 005.1  |2 23 
100 1 |a McIver, Annabelle.  |e author. 
245 1 0 |a Abstraction, Refinement and Proof for Probabilistic Systems  |h [electronic resource] /  |c by Annabelle McIver, Carroll Morgan. 
264 1 |a New York, NY :  |b Springer New York,  |c 2005. 
300 |a XX, 388 p. 63 illus.  |b online resource. 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
347 |a text file  |b PDF  |2 rda 
490 1 |a Monographs in Computer Science,  |x 0172-603X 
505 0 |a Probabilistic guarded commands and their refinement logic -- to pGCL: Its logic and its model -- Probabilistic loops: Invariants and variants -- Case studies in termination: Choice coordination, the dining philosophers, and the random walk -- Probabilistic data refinement: The steam boiler -- Semantic structures -- Theory for the demonic model -- The geometry of probabilistic programs -- Proved rules for probabilistic loops -- Infinite state spaces, angelic choice and the transformer hierarchy -- Advanced topics: Quantitative modal logic and game interpretations -- Quantitative temporal logic: An introduction -- The quantitative algebra of qTL -- The quantitative modal ?-calculus, and gambling games. 
520 |a 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. 
650 0 |a Computer science. 
650 0 |a Software engineering. 
650 0 |a Computer programming. 
650 0 |a Programming languages (Electronic computers). 
650 0 |a Computer logic. 
650 0 |a Mathematical logic. 
650 0 |a Probabilities. 
650 1 4 |a Computer Science. 
650 2 4 |a Software Engineering/Programming and Operating Systems. 
650 2 4 |a Probability Theory and Stochastic Processes. 
650 2 4 |a Programming Techniques. 
650 2 4 |a Logics and Meanings of Programs. 
650 2 4 |a Programming Languages, Compilers, Interpreters. 
650 2 4 |a Mathematical Logic and Formal Languages. 
700 1 |a Morgan, Carroll.  |e author. 
710 2 |a SpringerLink (Online service) 
773 0 |t Springer eBooks 
776 0 8 |i Printed edition:  |z 9780387401157 
830 0 |a Monographs in Computer Science,  |x 0172-603X 
856 4 0 |u http://dx.doi.org/10.1007/b138392  |z Full Text via HEAL-Link 
912 |a ZDB-2-SCS 
950 |a Computer Science (Springer-11645)