Abstract
In Business Process Modeling, several models are defined for the same system, supporting the transition from business requirements to IT implementations. Each of these models targets a different abstraction level and stakeholder perspective. In order to maintain consistency among these models, which has become a major challenge not only in this field, the correspondence between them has to be identified. A correspondence between process models establishes which activities in one model correspond to which activities in another model. This paper presents an algorithm for determining such correspondences. The algorithm is based on an empirical study of process models at a large company in the banking sector, which revealed frequent correspondence patterns between models spanning multiple abstraction levels. The algorithm has two phases, first establishing correspondences based on similarity of model element attributes such as types and names and then refining the result based on the structure of the models. Compared to previous work, our algorithm can recover complex correspondences relating whole process fragments rather than just individual activities. We evaluate the algorithm on 26 pairs of business-technical and technical-IT level models from four real-world projects, achieving overall precision of 93% and recall of 70%. Given the substantial recall and the high precision, the algorithm helps automating significant part of the correspondence recovery for such models.
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Castelo Branco, M., Troya, J., Czarnecki, K., Küster, J., Völzer, H. (2012). Matching Business Process Workflows across Abstraction Levels. In: France, R.B., Kazmeier, J., Breu, R., Atkinson, C. (eds) Model Driven Engineering Languages and Systems. MODELS 2012. Lecture Notes in Computer Science, vol 7590. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33666-9_40
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DOI: https://doi.org/10.1007/978-3-642-33666-9_40
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