STEREO: a SaT-based tool for an optimal solution of the sERvice selEctiOn problem
We present STEREO, a system that offers an expressive formalism and implements techniques firmly grounded on logic to solve the Service Selection Problem (SSP). STEREO adopts the Local-As-View approach (LAV) to represent services' functionality as views on ontology concepts, while user requests are expressed as conjunctive queries on these concepts. Additionally, users can describe their preferences, which are used to rank the solutions. We discuss the LAV formulation of SSP; then, we illustrate the encoding of SSP as a logical theory whose models are in correspondence with the problem solutions, and in presence of preferences, the best models are in correspondence with the best-ranked solutions. We demonstrate STEREO and the properties of modern SAT solvers that provide an efficient and scalable solution to SSP.