A theory of diagnosis from first principles
Artificial Intelligence
Artificial Intelligence
A correction to the algorithm in Reiter's theory of diagnosis
Artificial Intelligence
ACM Computing Surveys (CSUR)
A machine program for theorem-proving
Communications of the ACM
Chaff: engineering an efficient SAT solver
Proceedings of the 38th annual Design Automation Conference
Yet some more complexity results for default logic
Artificial Intelligence
Synthesizing Monitors for Safety Properties
TACAS '02 Proceedings of the 8th International Conference on Tools and Algorithms for the Construction and Analysis of Systems
SATO: An Efficient Propositional Prover
CADE-14 Proceedings of the 14th International Conference on Automated Deduction
From diagnosis to diagnosability: axiomatization, measurement and application
Journal of Systems and Software
Multiple Faults: Modeling, Simulation and Test
ASP-DAC '02 Proceedings of the 2002 Asia and South Pacific Design Automation Conference
Complexity results for explanations in the structural-model approach
Artificial Intelligence
Debugging Sequential Circuits Using Boolean Satisfiability
MTV '04 Proceedings of the Fifth International Workshop on Microprocessor Test and Verification
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In face of the unwieldiness of non-monotonic logic engines, or Prolog/CLP meta interpreters as they are commonly used for model based reasoning and diagnosis, this paper proposes a simple, but effective improvement for performing the complex diagnostic task. The chosen approach is twofold: firstly, the problem of contradicting first order system descriptions with a set of observations is reduced to propositional logic using the notion of symptoms, and secondly, the determination of conflict sets and minimal diagnoses is mapped to a problem whose technical solution has experienced a sheer boost over the past years, namely k-satisfiability using state-of-the-art SAT-solvers. Since the involved problems are (mostly) $\mathcal{NP}$-complete, the ideas for additional improvements for a more diagnosis-specific SAT-solver are also sketched and their implementation by means of a non-destructive solver, LSAT, evaluated.