Galois Releases Fully Automated SysML v1 to AADL Translation
Galois this week released fully automated SysML v1 to AADL data translation capabilities for our SysML to AADL Bridge Tool.
“Models are a great tool for design collaboration, but frequent model changes by a team of developers inevitably introduce design variations that need to be analyzed (and re-analyzed) over time,” explained Galois Research Engineer Ed Sandberg. “Automation of the SysML v1 to AADL process means teams can rapidly and frequently analyze models, and iterate on a design, leading to reduced revision churn.”
“Bottom line, this saves time and money,” added Galois Principal Scientist Tyler Smith. “With this enhancement to the Bridge Tool, users no longer have to manually export AADL models from SysML v1. Instead, they can translate models automatically in Docker.”
The System Modeling Language (SysML) was developed for Model-Based Systems Engineering (MBSE), allowing users to specify, analyze, design, verify, and validate a broad range of complex systems, from civil engineering projects to organization operations. The Architecture Analysis and Design Language (AADL) was developed as a domain specific language (DSL) for describing and modeling embedded computer systems architectures and associated equipment. Both modeling languages have strengths and limitations. Most notably, while AADL provides standard semantics within the embedded computing domain, SysML v1 does not. Among other things, using AADL standard semantics in models enables a variety of existing computer system architecture analysis, integration, and testing tools to be applied to models.
Galois’s SysML AADL Profile and SysML-to-AADL translation tools allow SysML v1 and AADL to be used together in a collaborative and synergistic way. The strengths of SysML v1 for overall systems engineering can be combined with the strengths of AADL for specifying and analyzing embedded computer subsystems within an overall system. Now that the translation tool can be fully automated, users can more easily and more quickly apply AADL-based analysis tools as part of a Model Development Operations (ModDevOps) toolchain.
We provide CAMET subscribers with a full working example of a GitLab runner job in a Docker container, but the code and steps are general enough to be used in the continuous integration environment of your choice.