Compliance validation and diagnosis of business data constraints in business processes at runtime |
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| Affiliation: | 1. Department of Languages and Computer Systems, University of Seville, Spain;2. Intelliment Security, Spain;1. Faculty of Engineering and Computer Science, Concordia University, Canada;2. Faculty of Computers and Information, Menofia University, Egypt;3. Department of Automatic Control and Systems Engineering, Sheffield University, UK;1. School of Computer Science and Engineering, Beihang University Beijing, No. 37 XueYuan Road, 100191 Beijing, China;2. School of Informatics, University of Edinburgh, 10 Crichton Street, Edinburgh EH8 9AB, United Kingdom;3. RCBD and SKLSDE Lab, Beihang University Beijing, No. 37 XueYuan Road, 100191 Beijing, China;4. Department of Mathematics and Computer Science, University of Antwerp, Middelheimlaan 1, B-2020 Antwerpen, Belgium;1. INRIA & LIRMM, University of Montpellier France;2. CNRS, LIG;1. School of Software, Tsinghua University, Beijing, China;2. Key Lab for Information System Security, Ministry of Education, Beijing, China;3. National Laboratory for Information Science and Technology, Beijing, China;4. Logistical Engineering University, Chongqing, China;5. Queensland University of Technology, Brisbane, Australia;6. Eindhoven University of Technology, Eindhoven, The Netherlands |
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| Abstract: | Business processes involve data that can be modified and updated by various activities at any time. The data involved in a business process can be associated with flow elements or data stored. These data must satisfy the business compliance rules associated with the process, where business compliance rules are policies or statements that govern the behaviour of a company. To improve and automate the validation and diagnosis of compliance rules based on the description of data semantics (called Business Data Constraints), we propose a framework where dataflow variables and stored data are analyzed. The validation and diagnosis process is automated using Constraint Programming, to permit the detection and identification of possibly unsatisfiable Business Data Constraints, even if the data involved in these constraints are not all instantiated. This implies that the potential errors can be determined in advance. Furthermore, a language to describe Business Data Constraints is proposed, for the improvement of user-oriented aspects of the business process description. This language allows a business expert to write Business Data Constraints that will be automatically validated in run-time, without the support of an information technology expert. |
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| Keywords: | Business processes validation and diagnosis Business data constraints Persistence data Constraint programming |
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