Constructing BPMN Process Model Behaviorally Equivalent to a Given Causal Net

<p>Process Mning discipline studies the relation between event log of a process and a model of this process. There is a number of tasks within the discipline, one of which is process discovery - extracting process model from an event log. Result of process discovery can be a model with multiple process anomalies that constrain further work with the model. To solve this problem causal nets are used, due to their semantics that ignores process anomalies. However, representation of causal nets can be not obvious for process analysists. On the other hand, there is BPMN-notation that is a de-facto standard for modeling business processes and comprehensible for a wide range of specialists. Therefore, the problem of converting causal net to BPMN-model is topical.</p><p>The aim of the work performed is to develop an algorithm of constructing BPMN-model that simulates the behaviour of a given causal net. The result of the work is the formal description of such algorithm and the proof of its correctness. Moreover, the algorithm was implemented within the plug-in BPMNConversions for process-aware information system ProM.</p>