Detecting and Preventing Power Outages in a Smart Grid using eMoflon

We present a solution to the Outage System Case of the Transformation Tool Contest 2017, based on the bidirectional model transformation language eMoflon. The case comprises two tasks, in which the goal is to produce custom model views on a set of input models from a smartgrid system, eventually allowing power outages to be detected and prevented. To facilitate understandability, our solution uses eMoflon’s declarative transformation rules. Moreover, to address performance, we use a general-purpose-language preprocessing step contributing to the identification of elements participating in the considered views.