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.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
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)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
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
Download citation
DOI: https://doi.org/10.1007/978-3-642-24749-1_5
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-24748-4
Online ISBN: 978-3-642-24749-1
eBook Packages: Computer ScienceComputer Science (R0)