Stochastic Automata Network of Modeling Parallel Systems
IEEE Transactions on Software Engineering
PEPS2007 - Stochastic Automata Networks Software Tool
QEST '07 Proceedings of the Fourth International Conference on Quantitative Evaluation of Systems
Semantics and analysis of business process models in BPMN
Information and Software Technology
ICFEM '08 Proceedings of the 10th International Conference on Formal Methods and Software Engineering
Modeling and analyzing resource-constrained business processes
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Formal analysis of BPMN via a translation into COWS
COORDINATION'08 Proceedings of the 10th international conference on Coordination models and languages
Performance analysis modeling applied to business processes
SpringSim '10 Proceedings of the 2010 Spring Simulation Multiconference
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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.