Detection and prediction of errors in EPCs of the SAP reference model

Abstract

Up to now there is neither data available on how many errors can be expected in process model collections, nor is it understood why errors are introduced. In this article, we provide empirical evidence for these questions based on the SAP reference model. This model collection contains about 600 process models expressed as Event-driven Process Chains (EPCs). We translated these EPCs into YAWL models, and analyzed them using the verification tool WofYAWL. We discovered that at least 34 of these EPCs contain errors. Moreover, we used logistic regression to show that complexity of EPCs has a significant impact on error probability.