Towards thresholds of control flow complexity measures for BPMN models

Business process models are considered to be a good mechanism for communication among stakeholders and are a key instrument in the analysis and design of information systems. It is therefore important to design business process models with a high level of quality, which can be discovered through measurement application. Several measurement initiatives exist in the literature, but these measures are only useful in real world decision making if we also have criteria with which to establish the goodness of models. We consider that measures with thresholds and decision criteria form indicators. Indicators allow us to make decisions by using the values of the measures which models should not exceed to ascertain whether the model is good in practice. In this paper we present the initial empirical results from which thresholds for the Control-Flow Complexity measure applied in BPMN models have been obtained according to the Bender method. Our findings reveal that there are different levels of understandability depending on the number of decision nodes: a very easily understandable model would have no more than 6 xor nodes, 1 or nodes and 1 and nodes, versus the 46 xor nodes, 14 or nodes and 7 and nodes which would constitute a model with a very difficult level of understandability.

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