Abstract
Verification of data-aware Business Processes is a highly complex and time consuming activity. As Business Processes tend to increase in terms of both size and complexity, the process of verifying such, becomes difficult even for experts. Data values may cause, for example, a deadlock in the control-flow of a Business Process, due to unsatisfied constraints on the data values, preventing the procedure of the process. Although commercial and non-commercial suites handling both control-flow and data-flow are available on the market, they struggle to produce an impact, due to the fact that the data-flow is on a separated layer from the control-flow.
In this paper we present the experimental results of the first prototype of the RAW-SYS framework, a framework for the verification of data-aware Business Processes, using small sized Business Process models, but arbitrarily complex, with updates on the data values and relying on data-constraints in order, for the process, to proceed. Despite the restricted size of the models, results are good and suggest that planning techniques are a valid way of verifying data-aware Business Processes.
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Sabiucciu, L., Montali, M., Tessaris, S. (2018). A Tool for the Verification of Data-Aware Business Processes. In: Ghidini, C., Magnini, B., Passerini, A., Traverso, P. (eds) AI*IA 2018 – Advances in Artificial Intelligence. AI*IA 2018. Lecture Notes in Computer Science(), vol 11298. Springer, Cham. https://doi.org/10.1007/978-3-030-03840-3_20
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DOI: https://doi.org/10.1007/978-3-030-03840-3_20
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