Transforming BPMN Processes to SBVR Process Rules with Deontic Modalities

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 th...

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Main Authors: Tomas Skersys, Paulius Danenas, Egle Mickeviciute, Rimantas Butleris
Format: Article
Language:English
Published: MDPI AG 2022-09-01
Series:Applied Sciences
Subjects:
Online Access:https://www.mdpi.com/2076-3417/12/18/8976
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author Tomas Skersys
Paulius Danenas
Egle Mickeviciute
Rimantas Butleris
author_facet Tomas Skersys
Paulius Danenas
Egle Mickeviciute
Rimantas Butleris
author_sort Tomas Skersys
collection DOAJ
description 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.
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spelling doaj.art-c39451a9cc2e41cebed6011deb4332142023-11-23T14:51:06ZengMDPI AGApplied Sciences2076-34172022-09-011218897610.3390/app12188976Transforming BPMN Processes to SBVR Process Rules with Deontic ModalitiesTomas Skersys0Paulius Danenas1Egle Mickeviciute2Rimantas Butleris3Center of Information Systems Design Technologies, Kaunas University of Technology, K. Barsausko Str. 59, 51423 Kaunas, LithuaniaCenter of Information Systems Design Technologies, Kaunas University of Technology, K. Barsausko Str. 59, 51423 Kaunas, LithuaniaCenter of Information Systems Design Technologies, Kaunas University of Technology, K. Barsausko Str. 59, 51423 Kaunas, LithuaniaCenter of Information Systems Design Technologies, Kaunas University of Technology, K. Barsausko Str. 59, 51423 Kaunas, LithuaniaThe 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.https://www.mdpi.com/2076-3417/12/18/8976business process modelprocess rulesmodel transformationSBVRBPMN
spellingShingle Tomas Skersys
Paulius Danenas
Egle Mickeviciute
Rimantas Butleris
Transforming BPMN Processes to SBVR Process Rules with Deontic Modalities
Applied Sciences
business process model
process rules
model transformation
SBVR
BPMN
title Transforming BPMN Processes to SBVR Process Rules with Deontic Modalities
title_full Transforming BPMN Processes to SBVR Process Rules with Deontic Modalities
title_fullStr Transforming BPMN Processes to SBVR Process Rules with Deontic Modalities
title_full_unstemmed Transforming BPMN Processes to SBVR Process Rules with Deontic Modalities
title_short Transforming BPMN Processes to SBVR Process Rules with Deontic Modalities
title_sort transforming bpmn processes to sbvr process rules with deontic modalities
topic business process model
process rules
model transformation
SBVR
BPMN
url https://www.mdpi.com/2076-3417/12/18/8976
work_keys_str_mv AT tomasskersys transformingbpmnprocessestosbvrprocessruleswithdeonticmodalities
AT pauliusdanenas transformingbpmnprocessestosbvrprocessruleswithdeonticmodalities
AT eglemickeviciute transformingbpmnprocessestosbvrprocessruleswithdeonticmodalities
AT rimantasbutleris transformingbpmnprocessestosbvrprocessruleswithdeonticmodalities