Compositional verification of knowledge-based systems: A case study for diagnostic reasoning

F.J. Cornelissen, C.M. Jonker, J. Treur

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

Abstract

In this paper a compositional verification method for models of knowledge-based systems is introduced. Required properties of the system are formally verified by deriving them from assumptions that themselves are properties of sub-components, which in their turn may be derived from assumptions on sub-sub-components, and so on. The method is based on properties that are formalised in terms of temporal semantics; both static and dynamic properties are covered. The compositional verification method imposes structure on the verification process. By the possibility to focus at one level of abstraction (information and process hiding), compositional verification provides transparency and limits the complexity per level. Since verification proofs are structured in a compositional manner, they can be reused in case of modification of the system. The method is illustrated for a generic model for diagnostic reasoning.
Original languageEnglish
Title of host publicationKnowledge Acquisition, Modeling and Management - 10th European Workshop, EKAW 1997, Proceedings
PublisherSpringer/Verlag
Pages65-80
Number of pages16
Volume1319
ISBN (Print)3540635920, 9783540635925
DOIs
Publication statusPublished - 1997
Event10th European Workshop on Knowledge Acquisition, Modeling and Management, EKAW 1997 - Sant Feliu de Guixols, Spain
Duration: 15 Oct 199718 Oct 1997

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume1319
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Workshop

Workshop10th European Workshop on Knowledge Acquisition, Modeling and Management, EKAW 1997
CountrySpain
CitySant Feliu de Guixols
Period15/10/9718/10/97

Keywords

  • compositional verification
  • knowledge-based systems
  • diagnostic reasoning model
  • formal compositional modelling

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