Testing Density as a Complexity Metric for EPCs

Measuring complexity of business process models is a rather new area of research. Since there are only a few contributions, it is not yet clear which metrics are needed in order to guide and increase the quality of model design. In this paper, we propose a density metric inspired by social network analysis in order to quantify the complexity of an EPC business process model on a scale between zero and one. In particular, we consider minimum and maximum number of arcs for a given set of function, event, and connector nodes. Furthermore, we test the EPC density metric in combination with simple metrics of size for its capability to predict errors in the SAP reference model. While the significance of density is promising, the experiment reveals that there are further metrics needed in addition to density.

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