000 04550nam a22004815i 4500
001 978-0-387-27006-7
003 DE-He213
005 20201213200354.0
007 cr nn 008mamaa
008 100301s2005 xxu| s |||| 0|eng d
020 _a9780387270067
_9978-0-387-27006-7
024 7 _a10.1007/b138392
_2doi
050 4 _aQA76.6-76.66
072 7 _aUM
_2bicssc
072 7 _aCOM051000
_2bisacsh
082 0 4 _a005.11
_223
100 1 _aMcIver, Annabelle.
_eauthor.
245 1 0 _aAbstraction, Refinement and Proof for Probabilistic Systems
_h[electronic resource] /
_cby Annabelle McIver, Carroll Morgan.
264 1 _aNew York, NY :
_bSpringer New York,
_c2005.
300 _aXIX, 383 p. 63 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aMonographs in Computer Science,
_x0172-603X
505 0 _aProbabilistic 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 _aProbabilistic 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 _aComputer science.
650 0 _aLogic design.
650 1 4 _aComputer Science.
650 2 4 _aProgramming Techniques.
650 2 4 _aLogics and Meanings of Programs.
650 2 4 _aProgramming Languages, Compilers, Interpreters.
650 2 4 _aMathematical Logic and Formal Languages.
700 1 _aMorgan, Carroll.
_eauthor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9780387401157
830 0 _aMonographs in Computer Science,
_x0172-603X
856 4 0 _uhttp://dx.doi.org/10.1007/b138392
912 _aZDB-2-SCS
950 _aComputer Science (Springer-11645)
999 _c12165
_d12165