The aim of this article is to present the AltaRica 3.0 project. "Traditional" risk modeling formalisms (e.g. Fault Trees, Markov Processes, etc.) are well mastered by safety analysts. Efficient assessment algorithms and tools are available. However, models designed with these formalisms are far from the specifications of the systems under study. They are consequently hard to design and to maintain throughout the life cycle of systems. The highlevel modeling language AltaRica has been created to tackle this problem. The objective of the AltaRica 3.0 project is to design a new version of AltaRica and to develop a complete set of authoring and assessment tools for this new version of the language. AltaRica 3.0 improves significantly the expressive power of AltaRica Data-Flow without decreasing the efficiency of assessment algorithms. Prototypes of a compiler to Fault Trees, a compiler to Markov chains, stochastic and stepwise simulators have been already developed. Other tools are under specification or implementation.

The aim of this article is to present the AltaRica 3.0 project. "Traditional" risk modeling formalisms (e.g. Fault Trees, Markov Processes, etc.) are well mastered by safety analysts. Efficient assessment algorithms and tools are available. However, models designed with these formalisms are far from the specifications of the systems under study. They are consequently hard to design and to maintain throughout the life cycle of systems. The highlevel modeling language AltaRica has been created to tackle this problem. The objective of the AltaRica 3.0 project is to design a new version of AltaRica and to develop a complete set of authoring and assessment tools for this new version of the language. AltaRica 3.0 improves significantly the expressive power of AltaRica Data-Flow without decreasing the efficiency of assessment algorithms. Prototypes of a compiler to Fault Trees, a compiler to Markov chains, stochastic and stepwise simulators have been already developed. Other tools are under specification or implementation.

The complexity of industrial systems is steadily increasing. To face this complexity, the different engineering disciplines are designing models. These models are complex as they reflect the complexity of systems under study. Therefore, they need to be structured.In this article we study structural constructs of modeling languages used in systems engineering. We introduce for that purpose a small domain specific language, the so-called S2ML for System Structure Modeling Language. We show that a large class of actual modeling languages can be (re)constructed by plugging their underlying mathematical framework into S2ML.