Enforcing Data-Aware Business Processes Using Execution Path-Oriented Strategies
Since the data-aware business process usually covers the control flow and data flow, and both of them have a direct impact on its execution, it is challenging to ensure its correctness. In this article, we propose a novel correctness enforcement approach for the data-aware business the processes. Given a data-aware business process, this approach first relies on the notion of the execution paths to capture all the parts of it that can be executed correctly. More specifically, it first splits the data-aware business process into a set of the execution paths, and then presents the notion of well-formedness to determine whether each execution path is correct. Based on these captured correct execution paths, an execution path-oriented strategy is generated, which is nonintrusive, and can enforce it to follow one of its correct execution paths during each execution, thereby realizing its correct execution. This approach is evaluated using the extensive experiments, which shows that it is effective and efficient, as well as scalable in practice.
Authors
- Fei Dai (ORCID: https://orcid.org/0000-0001-6469-357X)
- Qi Mo (ORCID: https://orcid.org/0000-0002-3438-5303)
- Jianeng Wang (ORCID: https://orcid.org/0009-0006-5268-0513)
- Zhongwen Xie (ORCID: https://orcid.org/0000-0002-3080-4881)
- Cong Liu (ORCID: https://orcid.org/0000-0002-5999-2126)
- Wei Wang (ORCID: https://orcid.org/0000-0002-2026-5378)
- Yi Jiang (ORCID: https://orcid.org/0000-0002-1420-1562)
Institutions
- Shandong University of Technology (CN)
- Yunnan University (CN)
- Southwest Forestry University (CN)
- Dalian University of Technology (CN)
- Taishan University (CN)
Publication Details
- Journal
- IEEE Transactions on Systems Man and Cybernetics Systems
- Published
- 2024-08-16
- DOI
- https://doi.org/10.1109/tsmc.2024.3427838
- Citations
- 1
- Primary Topic
- Business Process Modeling and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 0.53
Funders
- National Natural Science Foundation of China