The semantics of partial model transformations

Model transformations are traditionally designed to operate on models that do not contain uncertainty. In previous work, we have developed partial models, i.e., models that explicitly capture uncertainty. In this paper, we study the transformation of partial models. We define the notion of correct lifting of transformations so that they can be applied to partial models. For this, we encode transformations as transfer predicates and describe the mechanics of applying transformations using logic. We demonstrate the approach using two example transformations (addition and deletion) and outline a method for testing the application of transformations using a SAT solver. Reflecting on these preliminary attempts, we discuss the main limitations and challenges and outline future steps for our research on partial model transformation.