A theory of diagnosis from first principles
Artificial Intelligence
Symbolic Boolean manipulation with ordered binary-decision diagrams
ACM Computing Surveys (CSUR)
A theory of measurement in diagnosis from first principles
Artificial Intelligence
GRASP—a new search algorithm for satisfiability
Proceedings of the 1996 IEEE/ACM international conference on Computer-aided design
Efficient Intelligent Backtracking Using Linear Programming
INFORMS Journal on Computing
Diagnosing tree-decomposable circuits
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Deriving minimal conflict sets by CS-trees with mark set indiagnosis from first principles
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Interactive type debugging in Haskell
Haskell '03 Proceedings of the 2003 ACM SIGPLAN workshop on Haskell
Debugging Incoherent Terminologies
Journal of Automated Reasoning
Algorithms for maximum satisfiability using unsatisfiable cores
Proceedings of the conference on Design, automation and test in Europe
NMUS: Structural Analysis for Improving the Derivation of All MUSes in Overconstrained Numeric CSPs
Current Topics in Artificial Intelligence
Extracting MUCs from Constraint Networks
Proceedings of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy
QUICKXPLAIN: preferred explanations and relaxations for over-constrained problems
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Boosting a complete technique to find MSS and MUS thanks to a local search oracle
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Formal analysis and algorithms for extracting coordinate systems of games
CIG'09 Proceedings of the 5th international conference on Computational Intelligence and Games
Semantic email: theory and applications
Web Semantics: Science, Services and Agents on the World Wide Web
MUST: provide a finer-grained explanation of unsatisfiability
CP'07 Proceedings of the 13th international conference on Principles and practice of constraint programming
Measuring incoherence in description logic-based ontologies
ISWC'07/ASWC'07 Proceedings of the 6th international The semantic web and 2nd Asian conference on Asian semantic web conference
A heuristic local search algorithm for unsatisfiable cores extraction
ICCSA'07 Proceedings of the 2007 international conference on Computational science and its applications - Volume Part III
Automated diagnosis of feature model configurations
Journal of Systems and Software
On finding all minimally unsatisfiable subformulas
SAT'05 Proceedings of the 8th international conference on Theory and Applications of Satisfiability Testing
Discovery of minimal unsatisfiable subsets of constraints using hitting set dualization
PADL'05 Proceedings of the 7th international conference on Practical Aspects of Declarative Languages
SAT'06 Proceedings of the 9th international conference on Theory and Applications of Satisfiability Testing
Type processing by constraint reasoning
APLAS'06 Proceedings of the 4th Asian conference on Programming Languages and Systems
Synchronizing AMS Assertions with AMS Simulation: From Theory to Practice
ACM Transactions on Design Automation of Electronic Systems (TODAES)
SMT-based false positive elimination in static program analysis
ICFEM'12 Proceedings of the 14th international conference on Formal Engineering Methods: formal methods and software engineering
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An unsatisfiable set of constraints is minimal if all its (strict) subsets aresatisfiable.A number of forms of error diagnosis, including circuit error diagnosis and type error diagnosis, require finding all minimal unsatisfiable subsets of a given set of constraints (representing an error), in order to generate the best explanation of the error. In this paper we give algorithms for efficiently determining all minimal unsatisfiable subsets for any kind of constraints. We show how taking into account notions of independence of constraints and using incremental constraint solvers can significantly improve the calculation of these subsets.