Consistency-based diagnosis of configuration knowledge bases

dc.contributor.authorFelfernig, A.
dc.contributor.authorFriedrich, G.
dc.contributor.authorJannach, D.
dc.contributor.authorStumptner, M.
dc.date.issued2004
dc.description.abstractConfiguration problems are a thriving application area for declarative knowledge representation that currently experiences a constant increase in size and complexity of knowledge bases. Automated support of the debugging process of such knowledge bases is a necessary prerequisite for effective development of configurators. We show that this task can be achieved by consistency-based diagnosis techniques. Based on the formal definition of consistency-based configuration we develop a framework suitable for diagnosing configuration knowledge bases. During the test phase of configurators, valid and invalid examples are used to test the correctness of the system. In case such examples lead to unintended results, debugging of the knowledge base is initiated. Starting from a clear definition of diagnosis in the configuration domain we develop an algorithm based on conflicts. Our framework is general enough for its adaptation to diagnosing customer requirements to identify unachievable conditions during configuration sessions. A prototype implementation using commercial constraint-based configurator libraries shows the feasibility of diagnosis within the tight time bounds of interactive debugging sessions. Finally, we discuss the usefulness of the outcomes of the diagnostic process in different scenarios. © 2003 Elsevier B.V. All rights reserved.
dc.identifier.citationArtificial Intelligence, 2004; 152(2):213-234
dc.identifier.doi10.1016/S0004-3702(03)00117-6
dc.identifier.issn0004-3702
dc.identifier.issn1872-7921
dc.identifier.urihttps://hdl.handle.net/1959.8/26743
dc.language.isoen
dc.publisherElsevier BV
dc.rightsCopyright status unknown
dc.source.urihttps://doi.org/10.1016/S0004-3702(03)00117-6
dc.subjectdiagnosis
dc.subjectconfiguration
dc.titleConsistency-based diagnosis of configuration knowledge bases
dc.typeJournal article
pubs.publication-statusPublished
ror.mmsid9915912292101831

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