Return to search

Contextualized Programs for Ontology-Mediated Probabilistic System Analysis

Modeling context-dependent systems for their analysis is challenging as verification tools usually rely on an input language close to imperative programming languages which need not support description of contexts well. We introduce the concept of contextualized programs where operational behaviors and context knowledge are modeled separately using domain-specific formalisms. For behaviors specified in stochastic guarded-command language and contextual knowledge given by OWL description logic ontologies, we develop a technique to efficiently incorporate contextual information into behavioral descriptions by reasoning about the ontology. We show how our presented concepts support and facilitate the quantitative analysis of context-dependent systems using probabilistic model checking. For this, we evaluate our implementation on a case study issuing a multi-server system.

Identiferoai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:79605
Date20 June 2022
CreatorsDubslaff, Clemens, Koopmann, Patrick, Turhan, Anni-Yasmin
PublisherTechnische Universität Dresden
Source SetsHochschulschriftenserver (HSSS) der SLUB Dresden
LanguageEnglish
Detected LanguageEnglish
Typeinfo:eu-repo/semantics/acceptedVersion, doc-type:report, info:eu-repo/semantics/report, doc-type:Text
Rightsinfo:eu-repo/semantics/openAccess
Relationurn:nbn:de:bsz:14-qucosa2-785040, qucosa:78504

Page generated in 0.0021 seconds