T4A: Time4Sys for system architects
Bringing the power of timing analysis techniques directly into the system architect environment in order to help them to validate the design of their real time systems in early phase of development.
The solution extends the Capella system architecture environment and allows to define real time properties and constraints on the system in the early steps of design. Based on this information, the system architect can then launch analysis and simulations that validate the design and prove that the performance requirements will be met. If the design is invalid, the system architect will be guided to the specific parts that lead to invalid behaviours and need to be amended. The solution can be used in a generic engineering framework but also provides additional features for specific domains where timing is critical and where the complexity is such that it cannot be grasped by the human mind; an Arinc 653 customization supports this whole approach in the domain of integrated modular avionics so that a A653-based system architect could get timing analysis in a few clicks.
The FED4SAE partners provide real use cases where the approach is useful and real feedback from the trenches with value assessment (cost, planning, quality).
Since we believe the solution is relevant in many industrial fields, FED4SAE will support Artal in the definition and packaging of solutions for specific domains out of our existing scope of clients.
Developing a bridge between Capella and Time4Sys is a key factor for the adoption of Time4Sys in the industry. Since it is more and more adopted by aeronautics and space industry, and start to be used for teaching, for smart cities, smart health, smart building, smart transport and others. The resulting tooling from this experiment aims at improving the design of these systems, by giving confidence – and potentially proves – on the ability of the system to match the expected behavior; a power that was previously restricted to few specialists, late in the process, in the best case…
For critical systems, it will reduce the risk and associated costs of finding critical issue during the late stages of development and improve confidence on the system design. This will also support the optimization of the real time systems by reducing the security margins usually set to cope with the unforeseen chain of events leading to a failure.