(untitled) (Computer systems and information technologies, 2023)
This paper is devoted to solve the problem of analyzing the compliance of business process models with their textual descriptions. The problem being business process models describe re-designed or completely new organizational activities, but “wrong” models that do not reflect correctly business process requirements may mislead involved business process participants and other stakeholders, and cause workflow errors followed by extra costs. Therefore, the research goal is to ensure the correctness of business process models by analyzing their compliance with textual descriptions formulated by business process owners or business analysts. In the work, a review of existing tools for modeling and analysis of business processes is outlined, as well as the main technologies of natural language processing are considered, including tokenization, search for stop words, and stemming. These technologies are proposed to be used to analyze the compliance of business process models with their textual descriptions. An approach to solving the problem of analyzing the compliance of business process models with their textual descriptions, using the selected natural language processing tools is proposed and the respective algorithm is developed. The process of analyzing the compliance of business process models with their textual descriptions is formalized using data flow modeling. The corresponding software that implements this process is developed. Sample calculations are demonstrated that confirm the performance of the proposed approach by analyzing the model of the goods dispatch business process and the corresponding textual description of this business process. Finally, conclusions are given and the directions for further work are determined.