Automated performance analysis of business processes

Abstract

Business processes (BPs) can be seen as flows of tasks that are orchestrated to accomplish well-defined goals. The ability to predict at design time the BP behavior assumes a strategic relevance, both to early assess whether or not the business goals are achieved and to gain a competitive advantage. This paper focuses on the performance prediction of BPs. Specifically, this work introduces a model-driven method that, starting from a performance-enabled description of a BP, first derives a BP performance model of EQN (Extended Queueing Network) type, and then generates and executes the EQN model implementation, thus enacting a fully automated analysis of the business process behavior. The performance model implementation is carried out by use of jEQN, a java-based domain specific language for specifying and executing EQN models. The paper also describes how the proposed model-driven method has been effectively implemented.

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