РОЗРОБКА ПРОГРАМНОГО КОМПОНЕНТУ ДЛЯ ВИЯВЛЕННЯ ТА ОЦІНЮВАННЯ ЯКОСТІ ПАРАЛЕЛЬНИХ ШЛЮЗІВ У МОДЕЛЯХ BPMN НА ОСНОВІ НЕЧІТКОЇ ЛОГІКИ

The quality of business process models is a critical factor in ensuring the correctness, efficiency, and maintainability of information systems. Within the BPMN notation, which is nowadays a standard of business processes modeling, parallel (AND) gateways are of particular importance. Errors in their implementation, such as incorrect synchronization or termination of parallel branches, are common and difficult to detect by traditional metrics such as the Number of Activities (NOA) or Control-Flow Complexity (CFC). In this paper, we propose a method for evaluating the correctness of AND-gateways based on fuzzy logic using Gaussian membership functions. The proposed approach is implemented as a software component that analyzes BPMN models, provided in XML format, identifies all AND-gateways, and extracts structural characteristics, i.e. the numbers of incoming and outgoing sequence flows. This features are evaluated using “soft” modeling rules based on fuzzy membership functions. Additionally, an activation function with the 0.5 threshold is used to generate binary quality indicators and calculate an integral quality assessment measure. The software component is developed using Python, as well as third-party libraries: Pandas, NumPy, and Matplotlib. A set of 3729 BPMN models from the Camunda open source repository was used for experimental calculations. Of these, 1355 models contain 3171 AND-gateways. The obtained results demonstrate that 71.2% of the gateways are correct, and 28.8% have structural violations. In 50% of the models, the quality score is 1.00, which indicates high quality, however minimum values of 0.02 indicate the need for automated verification of business process models. The considered approach allows detecting AND-gateways modeling errors, increasing the reliability of BPMN models and offering the capabilities for intelligent business process modeling support.