FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W96703786> ?p ?o ?g. }

• W96703786 abstract "Predicate abstraction has become one of the most successful methodologies for proving safety properties of programs. Unfortunately, it cannot be used for verifying all liveness properties. In order to handle liveness properties, we introduce the method of ranking abstraction. This method augments the analyzed system by a “progress monitor” which observes whether a given ranking function decreases or increases at any step of the program. The fact that the ranking function ranges over a well-founded domain is expressed by a compassion (strong fairness) requirement, which states that a function over a well-founded domain cannot decrease infinitely many times without also increasing infinitely many times. In analogy to predicate abstraction which uses a predicate base $mathcal{P}$= {P1, ..., Pm} consisting of a set of predicates, we augment the program with a ranking coreΔ = {δ1,...,δn} consisting of several ranking components. The augmented system is then abstracted using standard predicate abstraction, but retaining all the compassion requirements. The abstracted augmented system is then model checked for an arbitrary ltl property. The ranking abstraction method is shown to be sound and (relatively) complete for proving all ltl properties, including safety and liveness.In the presented talk we focus on the strong analogy between predicate abstraction and ranking abstraction. Predicate abstraction can be viewed as a process which determines the best inductive invariant which can be formed as a boolean combination of the predicate base. In a similar way, ranking abstraction can be viewed as a search for the best well-founded global ranking function which can be formed as a lexicographic combination of the ranking components included in the ranking core Δ. In the talk, we present an algorithm for an explicit construction of such a global ranking function. Another important element of the predicate abstraction methodology is that of abstraction refinement by which, a coarse abstraction can be refined by analyzing a spurious counterexample. We show that ranking abstraction also possesses an analogous refinement process. We discuss how a spurious counter example can lead to a refinement of either the current predicate base or ranking core.The talk is based on results obtained through joint research with I. Balaban, Y. Kesten, and L.D. Zuck." @default.
• W96703786 created "2016-06-24" @default.
• W96703786 creator A5078214635 @default.
• W96703786 date "2005-01-01" @default.
• W96703786 modified "2023-09-23" @default.
• W96703786 title "Ranking Abstraction as a Companion to Predicate Abstraction" @default.
• W96703786 cites W1497571013 @default.
• W96703786 cites W1517320587 @default.
• W96703786 cites W1530375435 @default.
• W96703786 cites W1535168632 @default.
• W96703786 cites W1552505815 @default.
• W96703786 cites W2027755003 @default.
• W96703786 cites W2089139117 @default.
• W96703786 cites W2090398333 @default.
• W96703786 cites W2158395308 @default.
• W96703786 doi "https://doi.org/10.1007/11562948_1" @default.
• W96703786 hasPublicationYear "2005" @default.
• W96703786 type Work @default.
• W96703786 sameAs 96703786 @default.
• W96703786 citedByCount "1" @default.
• W96703786 crossrefType "book-chapter" @default.
• W96703786 hasAuthorship W96703786A5078214635 @default.
• W96703786 hasConcept C110251889 @default.
• W96703786 hasConcept C111472728 @default.
• W96703786 hasConcept C11413529 @default.
• W96703786 hasConcept C124304363 @default.
• W96703786 hasConcept C138885662 @default.
• W96703786 hasConcept C140146324 @default.
• W96703786 hasConcept C154945302 @default.
• W96703786 hasConcept C15569618 @default.
• W96703786 hasConcept C189430467 @default.
• W96703786 hasConcept C199360897 @default.
• W96703786 hasConcept C2779907942 @default.
• W96703786 hasConcept C2780654840 @default.
• W96703786 hasConcept C41008148 @default.
• W96703786 hasConcept C80444323 @default.
• W96703786 hasConceptScore W96703786C110251889 @default.
• W96703786 hasConceptScore W96703786C111472728 @default.
• W96703786 hasConceptScore W96703786C11413529 @default.
• W96703786 hasConceptScore W96703786C124304363 @default.
• W96703786 hasConceptScore W96703786C138885662 @default.
• W96703786 hasConceptScore W96703786C140146324 @default.
• W96703786 hasConceptScore W96703786C154945302 @default.
• W96703786 hasConceptScore W96703786C15569618 @default.
• W96703786 hasConceptScore W96703786C189430467 @default.
• W96703786 hasConceptScore W96703786C199360897 @default.
• W96703786 hasConceptScore W96703786C2779907942 @default.
• W96703786 hasConceptScore W96703786C2780654840 @default.
• W96703786 hasConceptScore W96703786C41008148 @default.
• W96703786 hasConceptScore W96703786C80444323 @default.
• W96703786 hasLocation W967037861 @default.
• W96703786 hasOpenAccess W96703786 @default.
• W96703786 hasPrimaryLocation W967037861 @default.
• W96703786 hasRelatedWork W1594482512 @default.
• W96703786 hasRelatedWork W1780369767 @default.
• W96703786 hasRelatedWork W1804882692 @default.
• W96703786 hasRelatedWork W2020850585 @default.
• W96703786 hasRelatedWork W2086991228 @default.
• W96703786 hasRelatedWork W2098376757 @default.
• W96703786 hasRelatedWork W2114684060 @default.
• W96703786 hasRelatedWork W2584099493 @default.
• W96703786 hasRelatedWork W36793001 @default.
• W96703786 hasRelatedWork W2181384782 @default.
• W96703786 isParatext "false" @default.
• W96703786 isRetracted "false" @default.
• W96703786 magId "96703786" @default.
• W96703786 workType "book-chapter" @default.