Consistency-based diagnosis of configuration knowledge bases

  • Authors:

  • Alexander Felfernig;Gerhard Friedrich;Dietmar Jannach;Markus Stumptner

  • Affiliations:

  • Universität Klagenfurt, Produktionsinformatik, A-9020 Klagenfurt, Austria;Universität Klagenfurt, Produktionsinformatik, A-9020 Klagenfurt, Austria;Universität Klagenfurt, Produktionsinformatik, A-9020 Klagenfurt, Austria;University of South Australia, Advanced Computing Research Centre, SA 5095 Adelaide, Australia

  • Venue:
  • Artificial Intelligence
  • Year:
  • 2004

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Abstract

Configuration 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.