A theory of diagnosis from first principles
Artificial Intelligence
Artificial Intelligence
Using crude probability estimates to guide diagnosis
Artificial Intelligence
Characterizing diagnoses and systems
Artificial Intelligence
GRASP—a new search algorithm for satisfiability
Proceedings of the 1996 IEEE/ACM international conference on Computer-aided design
A variant of Reiter's hitting-set algorithm
Information Processing Letters
Configuring Large Systems Using Generative Constraint Satisfaction
IEEE Intelligent Systems
The computation of hitting sets: review and new algorithms
Information Processing Letters
Consistency-based diagnosis of configuration knowledge bases
Artificial Intelligence
New approaches for efficient solution of hitting set problem
WISICT '04 Proceedings of the winter international synposium on Information and communication technologies
Planning, Scheduling And Constraint Satisfaction: From Theory To Practice
Planning, Scheduling And Constraint Satisfaction: From Theory To Practice
IEEE Intelligent Systems
Proceedings of the 13th international conference on Intelligent user interfaces
Automated debugging of recommender user interface descriptions
Applied Intelligence
QUICKXPLAIN: preferred explanations and relaxations for over-constrained problems
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Representative explanations for over-constrained problems
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
Computing minimal diagnoses by greedy stochastic search
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 2
Towards a generic model of configuraton tasks
IJCAI'89 Proceedings of the 11th international joint conference on Artificial intelligence - Volume 2
Hierarchical diagnosis of multiple faults
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Plausible repairs for inconsistent requirements
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
A general diagnosis method for ontologies
ISWC'05 Proceedings of the 4th international conference on The Semantic Web
Conflict-directed relaxation of constraints in content-based recommender systems
IEA/AIE'06 Proceedings of the 19th international conference on Advances in Applied Artificial Intelligence: industrial, Engineering and Other Applications of Applied Intelligent Systems
Resolving anomalies in configuration knowledge bases
ISMIS'12 Proceedings of the 20th international conference on Foundations of Intelligent Systems
Minimal sets over monotone predicates in boolean formulae
CAV'13 Proceedings of the 25th international conference on Computer Aided Verification
On computing minimal correction subsets
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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Constraint sets can become inconsistent in different contexts. For example, during a configuration session the set of customer requirements can become inconsistent with the configuration knowledge base. Another example is the engineering phase of a configuration knowledge base where the underlying constraints can become inconsistent with a set of test cases. In such situations we are in the need of techniques that support the identification of minimal sets of faulty constraints that have to be deleted in order to restore consistency. In this paper we introduce a divide and conquer-based diagnosis algorithm (FastDiag) that identifies minimal sets of faulty constraints in an overconstrained problem. This algorithm is specifically applicable in scenarios where the efficient identification of leading (preferred) diagnoses is crucial. We compare the performance of FastDiag with the conflict-directed calculation of hitting sets and present an in-depth performance analysis that shows the advantages of our approach.