Abstract
We present an approach for resolving inconsistencies in declarative process models while guaranteeing a minimal information loss (w.r.t. the number of deleted elements). To this aim, we show how smallest correction sets, i.e., the smallest sets of constraints that need to be deleted in order to resolve inconsistencies, can be computed via an application of Reiter’s hitting set theorem. In this context, as deleting certain constraints might be highly sensitive or not plausible in a real-life sense, we extend our approach with functionalities for enabling a close human-in-the-loop interaction, such as prioritizing constraints, as well as metrics that offer modelers insights into the impact of deleting constraints. Furthermore, we implement our approach and show that our inconsistency resolution approach outperforms existing approaches in terms of runtime and information loss in experiments with real-life data sets.
Part of the research project “Handling Inconsistencies in Business Process Modeling”, funded by the German Research Association (reference number: DE1983/9-1).
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Notes
- 1.
Given a model M and a corresponding constraint set C, a minimal inconsistent subset is defined as a set \(m\subseteq \mathbf{C} \), s.t. \(\mathcal {L}(m)=\emptyset \) and \(\not \exists m'\subset m\) with \(\mathcal {L}(m')=\emptyset \).
- 2.
The approach in [3] would behave analogously, except not by deleting constraints but iteratively building a new, maximally consistent model, which could also “drop” more constraints than necessary.
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- 4.
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- 7.
We acknowledge that the approach in [3] could have also been considered as a baseline; however, that approach cannot resolve quasi-inconsistencies and is therefore not fully comparable. Also, as the approach in [3] is also an approximation algorithm, it can be expected to also not compute the smallest possible number of deletions for all cases, which is why we consider the selected baseline [4] as representative.
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Corea, C., Nagel, S., Mendling, J., Delfmann, P. (2021). Interactive and Minimal Repair of Declarative Process Models. In: Polyvyanyy, A., Wynn, M.T., Van Looy, A., Reichert, M. (eds) Business Process Management Forum. BPM 2021. Lecture Notes in Business Information Processing, vol 427. Springer, Cham. https://doi.org/10.1007/978-3-030-85440-9_1
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