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Description
We present a novel approach for auditing conflicts between declarative constraints that arise during process execution, i.e., relative to observed traces. As a main advantage, taking a post-execution perspective allows to consider all observed traces and their interrelations, and to assess conflicts from a global perspective. Our approach allows to classify and prioritize conflicts as a basis for re-modelling, e.g., which conflicts are an outlier, and which require an urgent change to the model. Also, our approach provides means for quantitative root-cause analysis, i.e., prioritizing which rules need to be changed. We implement our approach and show that it can be applied in settings of industrial scale by means of runtime experiments with real-life data-sets.
Recommended Citation
Corea, Carl; Mansour, Rana; and Delfmann, Patrick, "Advanced Auditing of Run-Time Conflicts in Declarative Process Models using Time Series Clustering" (2022). Wirtschaftsinformatik 2022 Proceedings. 4.
https://aisel.aisnet.org/wi2022/design_science/design_science/4
Advanced Auditing of Run-Time Conflicts in Declarative Process Models using Time Series Clustering
We present a novel approach for auditing conflicts between declarative constraints that arise during process execution, i.e., relative to observed traces. As a main advantage, taking a post-execution perspective allows to consider all observed traces and their interrelations, and to assess conflicts from a global perspective. Our approach allows to classify and prioritize conflicts as a basis for re-modelling, e.g., which conflicts are an outlier, and which require an urgent change to the model. Also, our approach provides means for quantitative root-cause analysis, i.e., prioritizing which rules need to be changed. We implement our approach and show that it can be applied in settings of industrial scale by means of runtime experiments with real-life data-sets.