Cluster-Based Constraint Ordering for Direct Diagnosis

Müslüm Atas, Alexander Felfernig, Seda Polat Erdeniz, Stefan Reiterer, Amal Shehadeh, Thi Ngoc Trang Tran

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


Prediction quality and runtime performance are important performance indicators for diagnosis algorithms. In this paper, we propose a new method (ClusDiag) Cluster-Based Constraint Ordered Direct Diagnosis}) which can improve both indicators. ClusDiag has a learning phase to find a constraint ordering heuristic. After the learning phase, a diagnosis is found by applying the direct diagnosis algorithm FastDiag on an inconsistent constraint set where the constraints are reordered with respect to the constraint ordering heuristic.
Original languageEnglish
Title of host publication19th International Configuration Workshop
Subtitle of host publicationProceedings
Place of PublicationParis
Number of pages4
ISBN (Electronic)978-2-9516606-2-5
Publication statusPublished - 2017
Event19th International Configuration Workshop - La Defense, Paris, France
Duration: 14 Sept 201715 Sept 2017


Workshop19th International Configuration Workshop
Abbreviated titleCWS2017
Internet address


  • Configuration Systems
  • Performance Optimization
  • Clustering
  • Diagnosis
  • Variable and Value Ordering Heuristics
  • Constraint Satisfaction


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