Towards quality driven exploration of model transformation spaces

Verifying that a software system has certain nonfunctional properties is a primary concern in many engineering fields. Although several model-driven approaches exist to predict quality attributes from system models, they still lack the proper level of automation envisioned by Model Driven Software Development. When a potential issue concerning non-functional properties is discovered, the identification of a solution is still entirely up to the engineer and to his/her experience. This paper presents QVT-Rational, our multi-modeling solution to automate the detection-solution loop. We leverage and extend existing model transformation techniques with constructs to elicit the space of the alternative solutions and to bind quality properties to them. Our framework is highly customizable, it supports the definition of nonfunctional requirements and provides an engine to automatically explore the solution space. We evaluate our approach by applying it to two well-known software engineering problems -- Object-Relational Mapping and components allocation -- and by showing how several solutions that satisfy given performance requirements can be automatically identified.