State Propagation in Abstracted Business Processes
Business process models are abstractions of concrete operational procedures that occur in the daily business of organizations. Typically one model is insufficient to describe one business process. For instance, a detailed technical model may enable automated process execution, while a more abstract model supports decision making and process monitoring by business users. Thereafter, multiple models capturing one process at various levels of abstraction often coexist. While the relations between such models are studied, little is known about the relations between process instances and abstract models.
In this paper we show how the state of an abstract activity can be calculated from the states of related, detailed process activities as they happen. The approach uses activity state propagation. With state uniqueness and state transition correctness we introduce formal properties that improve the understanding of state propagation. Algorithms to check these properties are devised. Finally, we use behavioral profiles to identify and classify behavioral inconsistencies in abstract process models that might occur, once activity state propagation is used.
KeywordsBusiness Process Abstract Model Process Instance Activity Instance Prepare Data
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- 4.Bobrik, R., Reichert, M., Bauer, T.: Parameterizable Views for Process Visualization. Technical Report TR-CTIT-07-37, Centre for Telematics and Information Technology, University of Twente, Enschede (April 2007)Google Scholar
- 6.Di Francescomarino, C., Marchetto, A., Tonella, P.: Cluster-based Modularization of Processes Recovered from Web Applications. Journal of Software Maintenance and Evolution: Research and Practice (2010)Google Scholar
- 12.Knoepfel, A., Groene, B., Tabeling, P.: Fundamental Modeling Concepts: Effective Communication of IT Systems. John Wiley & Sons, Ltd. (2005)Google Scholar
- 18.van Glabbeek, R.J.: The Linear Time-Branching Time Spectrum (Extended Abstract). In: Baeten, J.C.M., Klop, J.W. (eds.) CONCUR 1990. LNCS, vol. 458, pp. 278–297. Springer, Heidelberg (1990)Google Scholar
- 23.Weidlich, M., Mendling, J., Weske, M.: Efficient Consistency Measurement based on Behavioural Profiles of Process Models. In: IEEE TSE (2010) (to appear)Google Scholar
- 25.zur Muehlen, M.: Workflow-based Process Controlling - Foundation, Design and Application of Workflow-Driven Process Information Systems. PhD thesis, University of Münster (2002)Google Scholar