Detecting Common Errors in Event-Driven Process Chains by Label Analysis
AbstractIn this article, we discuss several classes of error patterns that can frequently be found in Event-Driven Process Chains (EPC). Instances of these patterns can be detected by using a pattern-matching approach: The model is translated into a set of Prolog rules and potential modelling problems are located by querying the Prolog fact base for certain problem patterns. In particular, this article presents patterns for problems that can be detected by analysing the labels of events and functions in EPCs. To make reasoning about the contents of the labels possible, the labels are transformed into a normal form. By taking synonyms, antonyms and negating words (no, not) into account, we locate labels that contradict each other. This leads to the detection of some classes of errors like modelling of an event and its negation occurring at the same time. Our method has been applied to 1253 EPC models in German language. We have been able to detect a large number of errors in those models that remain undetected using traditional approaches for EPC validation.
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