Availability-Driven Architectural Change Propagation Through Bidirectional Model Transformations Between UML and Petri Net Models

Software architecture is nowadays subject to frequent changes due to multiple reasons, such as evolution induced by new requirements. Architectural changes driven by non-functional requirements are particularly difficult to identify, because they attain quantitative analyses that are usually carried out with specific languages and tools. A considerable number of approaches, based on model transformations, have been proposed in the last decades to derive non-functional models from software architectural descriptions. However, there is a clear lack of automation in the backward path that brings the analysis results back to the software architecture. In this paper we address this problem in the context of software availability. We introduce a bidirectional model transformation between UML State Machines (SM), annotated with availability properties, and Generalized Stochastic Petri Nets (GSPN). Such transformation, implemented in the JTL language, is used both to derive a GSPN-based availability model from a SM-based software architecture and, after the analysis, to propagate back on the SM the changes carried out on the GSPN. We demonstrate the effectiveness of our approach on an Environmental Control System to which we apply well-known fault tolerance patterns aimed at improving its software availability.