Table A1 summarizes the various characteristics of the synthetic models used in the experiments, including the number of event types, the size of the state space, whether a challenging construct is contained (loops, duplicates, nonlocal choice, and concurrency), and the entropy of the process defined by the model (estimated based on a sample of size 10,000). The original models may contain either duplicate tasks (two conceptually different transitions with the same label) or invisible tasks (transitions that have no label, as their firing is not recorded in the event log). We transformed all invisible transitions to duplicates such that, when there was an invisible task i in the original model, we added duplicates for all transitions t that, when fired, enable the invisible transition. These duplicates emulate the combined firing of t and i. Since we do not distinguish between duplicates and invisible tasks, we combined this category.

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With a steady increase of regulatory requirements for business processes, automation support of compliance management is a field garnering increasing attention in Information Systems research. Several approaches have been developed to support compliance checking of process models. One major challenge for such approaches is their ability to handle different modeling techniques and compliance rules in order to enable widespread adoption and application. Applying a structured literature search strategy, we reflect and discuss compliance-checking approaches in order to provide an insight into their generalizability and evaluation. The results imply that current approaches mainly focus on special modeling techniques and/or a restricted set of types of compliance rules. Most approaches abstain from real-world evaluation which raises the question of their practical applicability. Referring to the search results, we propose a roadmap for further research in model-based business process compliance checking.

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