Abstract
The qualitative and quantitative analysis of operational processes recently started to receive special attention with the business process management systems. But the Business Process Model and Notation (BPMN), the standard representation of business processes, is not the most appropriate kind of model to support the analysis phase. Most of the works proposing mappings from BPMN to formal languages aim model verification, but few are directed to quantitative analysis. In this work, we state that a well-defined BPMN Process diagram can originate a Stochastic Automata Network (SAN) – a compositionally built stochastic model. More than support verification, SAN provides a numerical evaluation of processes’ performance. SAN attenuates the state-space explosion problem associated with other Markovian formalisms and is used to model large systems. We defined an algorithm that automatically converts BPMN diagrams to SAN models. With these SAN models, we make analytical performance evaluations of business processes.
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References
Braghetto, K.R., Ferreira, J.a.E., Vincent, J.M.: Performance analysis modeling applied to business processes. In: 2010 Spring Simulation Multiconference, pp. 122:1–122:8. SCS/ACM, New York (2010)
Brenner, L., Fernandes, P., Plateau, B., Sbeity, I.: PEPS2007 - stochastic automata networks software tool. In: 4th International Conference on Quantitative Evaluation of Systems, pp. 163–164. IEEE Computer Society, Washington (2007)
Canevet, C., Gilmore, S., Hillston, J., Prowse, M., Stevens, P.: Performance modelling with the unified modelling language and stochastic process algebras. IEE Proceedings Computers and Digital Techniques 150(2), 107–120 (2003)
Dijkman, R.M., Dumas, M., Ouyang, C.: Semantics and analysis of business process models in BPMN. Information and Software Technology 50(12), 1281–1294 (2008)
Oliveira, C., Lima, R., Andre, T., Reijers, H.A.: Modeling and analyzing resource-constrained business processes. In: 2009 IEEE International Conference on Systems, Man and Cybernetics, pp. 2824–2830. IEEE Press, Los Alamitos (2009)
OMG: BPMN 2.0 by example, version 1.0 (non-normative) (2011)
OMG: Business process model and notation (BPMN), version 2.0 (2011)
Plateau, B.: On the stochastic structure of parallelism and synchronization models for distributed algorithms. SIGMETRICS Perform. Eval. Rev. 13(2), 147–154 (1985)
Plateau, B., Atif, K.: Stochastic automata network for modeling parallel systems. IEEE Transactions on Software Engineering 17(10), 1093–1108 (1991)
Prandi, D., Quaglia, P., Zannone, N.: Formal analysis of BPMN via a translation into COWS. In: Wang, A.H., Tennenholtz, M. (eds.) COORDINATION 2008. LNCS, vol. 5052, pp. 249–263. Springer, Heidelberg (2008)
Wong, P.Y.H., Gibbons, J.: A process semantics for BPMN. In: Liu, S., Araki, K. (eds.) ICFEM 2008. LNCS, vol. 5256, pp. 355–374. Springer, Heidelberg (2008)
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Braghetto, K.R., Ferreira, J.E., Vincent, JM. (2011). Performance Evaluation of Business Processes through a Formal Transformation to SAN. In: Thomas, N. (eds) Computer Performance Engineering. EPEW 2011. Lecture Notes in Computer Science, vol 6977. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24749-1_5
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DOI: https://doi.org/10.1007/978-3-642-24749-1_5
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