Synthesis of state machine models.

The automated synthesis of behavioural models in the form of state machines (SMs) from higher-level specifications has a high potential impact on the efficiency and accuracy of software development using models. In this paper, inspired by program synthesis techniques, we propose a model synthesis approach that takes as input a structural model of a system and its desired system properties, and automatically synthesizes executable SMs for its components. To this end, we first generate a synthesis formula for each component, consistent with the system properties, and then perform a State Space Exploration (SSE) of each component, based on its synthesis formula. The result of the SSE is saved in a Labeled Transition System (LTS), for which we then synthesize detailed actions for each of its transitions. Finally, we transform the LTSs into UML-RT (UML real-time profile) SMs, and integrate them with the original structural models. We assess the applicability, performance, and scalability of our approach using several different use cases extracted from the literature.