Abstract
Formal verification is a process to ensure that the business process model and notation (BPMN) design model is free of deadlock, livelock, and other undesirable properties that can cause a system crash. Formal verification is a complicated procedure involving model abstraction and model checking tools used for property checking. There are several existing transformation techniques that yield an abstract model, but the data perspective is not considered. These techniques are also inappropriate for the large-scale BPMN design model. An automated transformation can reduce the flaws, time consumption, and complexity of the large-scale BPMN design model. This paper proposes a transformation technique and provides a framework for transforming the BPMN design models into colored Petri nets (CPNs). Our techniques cover both the control-flow and data-flow perspectives. The partitioning technique of the BPMN design model is applied to reduce the complexity and leads to a CPN model that can support the hierarchical and compositional verification techniques that are suitable for the large-scale BPMN design models. The proposed transformation has been implemented as a transformation framework and is able to consistently transform the BPMN design models into CPN models.
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