Performance evaluation of business processes through a formal transformation to SAN

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. © 2011 Springer-Verlag.