Title Transforming BPMN processes to SBVR process rules with deontic modalities /
Authors Skersys, Tomas ; Danenas, Paulius ; Mickeviciute, Egle ; Butleris, Rimantas
DOI 10.3390/app12188976
Full Text Download
Is Part of Applied sciences.. Basel : MDPI. 2022, vol. 12, iss. 18, art. no. 8976, p. 1-27.. ISSN 2076-3417
Keywords [eng] business process model ; process rules ; model transformation ; SBVR ; BPMN
Abstract [eng] The Object Management Group (OMG) has put considerable effort into the standardization of various business modeling aspects within the context of model-driven systems development. Indeed, the Business Process Model and Notation (BPMN) is now arguably the most popular process modeling language. At the same time, the Semantics of Business Vocabulary and Business Rules (SBVR), which is a novel and formally sound standard for the specification of virtually any kind of knowledge using controlled natural language, is also gaining its grounds. Nonetheless, the integration between these two very much related standards remains weak. In this paper, we present one such integration effort, namely an approach for the extraction of SBVR process rules from BPMN processes. To accomplish this, we utilized model-to-model transformation technology, which is one of the core features of Model-Driven Architecture. At the core of the presented solution stands a set of model transformation rules and two algorithms specifying the formation of formally defined process rules from process models. Basic implementation aspects, together with the source code of the solution, are also presented in the paper. The experimental results acquired from the automatic model transformation have shown full compliance with the benchmark results and cover the entirety of the specified flow of work defined in the experimental process models. Following this, it is safe to conclude that the set of specified transformation rules and algorithms was sufficient for the given scope of the experiment, providing a solid background for the practical application and future developments of the solution.
Published Basel : MDPI
Type Journal article
Language English
Publication date 2022
CC license CC license description