The size and complexity of software in spacecraft is increasing exponentially, and this trend complicates its validation within the context of the overall spacecraft system. Current validation methods are labor-intensive as they rely on manual analysis, review and inspection. For future space missions, we developed -with challenging requirements from the European space industry -a novel modeling language and toolset for a (semi-)automated validation approach. Our modeling language is a dialect of AADL and enables engineers to express the system, the software, and their reliability aspects. The COMPASS toolset utilizes state-of-the-art model checking techniques, both qualitative and probabilistic, for the analysis of requirements related to functional correctness, safety, dependability and performance. Several pilot projects have been performed by industry, with two of them having focused on the system-level of a satellite platform in development. Our efforts resulted in a significant advancement of validating spacecraft designs from several perspectives, using a single integrated system model. The associated technology readiness level increased from level 1 (basic concepts and ideas) to early level 4 (laboratory-tested).

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Abstract-Safety assessment of dependable systems is a complex verification task that is desirable to be explicitly incorporated into the development cycle during the very early stages of a project. The main reason is that the cost to correct a safety error at the late stages of system development is excessively high. Towards this aim, we introduce an ontologybased model-driven engineering process for automating transformations of models that are utilized as reusable artifacts. The logical and syntactical structures of the design and safety models have to conform to a number of metamodel constraints. These constraints are semantically represented by mapping them onto an OWL domain ontology, allowing the incorporation of a Description Logic OWL reasoner and inference rules, in order to detect lacks of model elements and semantically inconsistent parts. Model validation throughout the ontology-based transformation assures that the generated formal safety model fulfils a series of requirements that render it analyzable. Our approach has been implemented as a response to an industrial problem 1 , where the architecture design is expressed in Architecture Analysis and Design Language (AADL) and safety models are specified in the AltaRica formal language.