Abstract
Although it is not considered good practice, many process models from practice contain detailed decision logic, encoded through control flow structures. This often results in spaghetti-like and complex process models and reduces maintainability of the models. In this context, the OMG proposes to use the Decision Model and Notation (DMN) in combination with BPMN in order to reach a separation of concerns. This paper introduces a semi-automatic approach to (i) identify decision logic in process models, (ii) to derive a corresponding DMN model and to adapt the original process model by replacing the decision logic accordingly, and (iii) to allow final configurations of this result during post-processing. This approach enables business organizations to migrate already existing BPMN models. We evaluate this approach by implementation, semantic comparison of the decision taking process before and after approach application, and an empirical analysis of industry process models.
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Batoulis, K., Meyer, A., Bazhenova, E., Decker, G., Weske, M. (2015). Extracting Decision Logic from Process Models. In: Zdravkovic, J., Kirikova, M., Johannesson, P. (eds) Advanced Information Systems Engineering. CAiSE 2015. Lecture Notes in Computer Science(), vol 9097. Springer, Cham. https://doi.org/10.1007/978-3-319-19069-3_22
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DOI: https://doi.org/10.1007/978-3-319-19069-3_22
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