Thresholds for error probability measures of business process models

Jan Mendling, Laura Sanchez-Gonzalez, Felix Garcia, Marcello La Rosa

Publication: Scientific journalJournal articlepeer-review

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The quality of conceptual business process models is highly relevant for the design of corresponding information systems. In particular, a precise measurement of model characteristics can be beneficial from a business perspective, helping to save costs thanks to early error detection. This is just as true from a software engineering point of view. In this latter case, models facilitate stakeholder communication and software system design. Research has investigated several proposals as regards measures for business process models, from a rather correlational perspective. This is helpful for understanding, for example size and complexity as general driving forces of error probability. Yet, design decisions usually have to build on thresholds, which can reliably indicate that a certain counter-action has to be taken. This cannot be achieved only by providing measures; it requires a systematic identification of effective and meaningful thresholds. In this paper, we derive thresholds for a set of structural measures for predicting errors in conceptual process models. To this end, we use a collection of 2,000 business process models from practice as a means of determining thresholds, applying an adaptation of the ROC curves method. Furthermore, an extensive validation of the derived thresholds was conducted by using 429 EPC models from an Australian financial institution. Finally, significant thresholds were adapted to refine existing modeling guidelines in a quantitative way.
Original languageEnglish
Pages (from-to)1188-1197
JournalJournal of Systems and Software
Issue number5
Publication statusPublished - 1 Oct 2012

Austrian Classification of Fields of Science and Technology (ÖFOS)

  • 502050 Business informatics

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