Quality Prediction of Service Compositions through Probabilistic Model Checking

The problem of composing services to deliver integrated business solutions has been widely studied in the last years. Besides addressing functional requirements, services compositions should also provide agreed service levels. Our goal is to support model-based analysis of service compositions, with a focus on the assessment of non-functional quality attributes, namely performance and reliability. We propose a modeldriven approach, which automatically transforms a design model of service composition into an analysis model, which then feeds a probabilistic model checker for quality prediction. To bring this approach to fruition, we developed a prototype tool called ATOP, and we demonstrate its use on a simple case study.