Complexity metrics for process models - A systematic literature review

ContextOne of the focal purposes of using visual process models (i.e. process diagrams) is to ensure easier, universally understood and unambiguous diagrammatic communication. Thus the models should be easy to comprehend and maintain, which is directly related to their complexity. In order to systematically address process models complexity, it has to be measured. ObjectiveThe goal of our work was to provide a better overview and understanding in the field of process models complexity and to provide an overview of the corresponding metrics. MethodA systematic literature review (SLR) was conducted, being the most suitable method for achieving aforementioned goals. In addition, to answer the stated research questions, different techniques for qualitative and quantitative data analysis and synthesis were used. ResultsWe identified 43 relevant articles which were systematically analyzed according to a pre-defined process and data acquisition form. Out of these articles we collected 66 process models complexity metrics. ConclusionModelers can use the catalogue of process complexity metrics to establish and ensure good quality of diagrams, whereas researches can relate to or extend the catalogue by providing new metrics or new insights to existing ones. 65 Process complexity metrics were systematically identified and analyzed.We primary analyzed their basis, approach, used constructs and validity.All metrics were visually represented according to the underlying theory and domain.Interrelationships between metrics were presented in a graph-based diagram.

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