Detection of naming convention violations in process models for different languages

Companies increasingly use business process modeling for documenting and redesigning their operations.
However, due to the size of such modeling initiatives, they often struggle with the quality assurance of their
model collections. While many model properties can already be checked automatically, there is a notable gap
of techniques for checking linguistic aspects such as naming conventions of process model elements. In this
paper, we address this problem by introducing an automatic technique for detecting violations of naming
conventions. This technique is based on text corpora and independent of linguistic resources such as WordNet.
Therefore, it can be easily adapted to the broad set of languages for which corpora exist. We demonstrate the
applicability of the technique by analyzing nine process model collections from practice, including over 27,000
labels and covering three different languages. The results of the evaluation show that our technique yields
stable results and can reliably deal with ambiguous cases. In this way, this paper provides an important
contribution to the field of automated quality assurance of conceptual models.