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.
|Title of host publication||19th International Configuration Workshop|
|Subtitle of host publication||Proceedings|
|Place of Publication||Paris|
|Number of pages||4|
|Publication status||Published - 2017|
|Event||19th International Configuration Workshop - La Defense, Paris, France|
Duration: 14 Sep 2017 → 15 Sep 2017
|Workshop||19th International Configuration Workshop|
|Period||14/09/17 → 15/09/17|
- Configuration Systems
- Performance Optimization
- Variable and Value Ordering Heuristics
- Constraint Satisfaction
Atas, M., Felfernig, A., Polat Erdeniz, S., Reiterer, S., Shehadeh, A., & Tran, T. N. T. (2017). Cluster-Based Constraint Ordering for Direct Diagnosis. In 19th International Configuration Workshop : Proceedings (pp. 68-71). Paris.