Abstract
The quality of business process models is an increasing concern as enterprise-wide modelling initiatives have to rely heavily on non-expert modellers. Quality in this context can be directly related to the actual usage of these process models, in particular to their understandability and modifiability. Since these attributes of a model can only be assessed a posteriori, it is of central importance for quality management to identify significant predictors for them. A variety of structural metrics have recently been proposed, which are tailored to approximate these usage characteristics. In this paper, we address a gap in terms of validation for metrics regarding understandability and modifiability. Our results demonstrate the predictive power of these metrics. These findings have strong implications for the design of modelling guidelines.
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Sánchez-González, L., García, F., Mendling, J., Ruiz, F., Piattini, M. (2010). Prediction of Business Process Model Quality Based on Structural Metrics. In: Parsons, J., Saeki, M., Shoval, P., Woo, C., Wand, Y. (eds) Conceptual Modeling – ER 2010. ER 2010. Lecture Notes in Computer Science, vol 6412. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16373-9_35
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DOI: https://doi.org/10.1007/978-3-642-16373-9_35
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