GigMaleBPMN: Generation of Graphical Components from the BPMN Model Using Machine Learning

The BPMN model allows organizations to depict business processes. However, this model does not capture the functional behavior of the system to generate graphical components. This article proposes a method for generating graphical components from a BPMN model using Machine Learning. The method is structured in four steps: (1) creating a BPMN model, (2) using Machine Learning to identify the elements of the BPMN model and indicate which graphical components should be used, (3) manually developing wireframes in Balsamiq based on the identified BPMN elements, and (4) using Machine Learning to identify the graphical components of the wireframes, enabling the automatic generation of graphical components and code. To enhance understanding, an illustrative example was developed using the method. The results prove that this approach allows for the automatic generation of graphical components using Machine Learning from a BPMN model.