Model-Based Diagnosis Meets Combinatorial Testing For Generating an Abductive Diagnosis Model

The diagnostic model is certainly a key element for any model-based diagnosis process. Experience shows though that in practice we often have no such model available for one or the other reason. The consequence for many projects is thus that we cannot draw on diagnosis processes when tackling problems. In this paper, we show how to improve available automated processes for deriving a diagnostic model from the standard simulation models that we usually create during development. We delve in particular into the question how research in the context of combinatorial testing and fault injection can help to improve the process, and consider several questions that arise.