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The Boolean approach to computing minimal hitting sets proposed by Lin and Jiang is known to offer very attractive general performance, but also has its issues, specifically with a cardinality-restricted search. In this paper we propose optimizations regarding the refinement rules, also offering a revised decision strategy as well as optimized termination(More)
Diagnosis, i.e., the identification of root causes for failing or unexpected system behavior, is an important task in practice. Within the last three decades, many different AI-based solutions for solving the diagnosis problem have been presented and have been gaining in attraction. This leaves us with the question of which algorithm to prefer in a certain(More)
Complementing recent research regarding the direct computation of diagnoses in theorem provers, complete hitting set algorithms are still an essential technique in the context of model-based diagnosis. Besides deriving diagnoses from available conflicts, they may even drive the search for those unsatisfiable cores in the problem description. Thus a series(More)
Automated assistance in ensuring a product's reliability and functional correctness is certainly a powerful asset, but also requires us to express our expectations in a formal way as accessible to our algorithms and tools. In recent work, we showed for specifications in Pnueli's "Temporal Logic of Programs" LTL how to diagnose such a specification if we(More)
For a wide selection of problems, characterizing them as a group of sets allows us to derive desired solutions by computing their minimal hitting sets. For his approach at model-based diagnosis, for instance, Raymond Reiter suggested to compute diagnoses as minimal hitting sets of encountered conflicts between behavioral assumptions, and defined a(More)
In this paper we present an approach for automatically deriving test input data from Design by Contract specifications. Preconditions of a method under test (MUT) require specific object states of the input parameters. In this paper we present IntiSa, a novel approach, which calculates test input values to be used with mock objects. The calculated values do(More)
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