Coding with AADL
November 2014 • Podcast
Julien Delange Interviewer Suzanne Miller
In this podcast, Julien Delange summarizes different perspectives on research related to code generation from software architecture models.
One of the challenges in product line deployment and maintenance is managing the variation and making sure you understand whether you have deployed the correct configuration to each individual instance. So, AADL can be the home of the performance parameters, the different configuration settings that are related to each of the different environmental instances. Oh, that is very cool.
Software Engineering Institute
Given that up to 70 percent of system errors are introduced during the design phase, stakeholders need a modeling language that will ensure both requirements enforcement during the development process and the correct implementation of these requirements. Previous work demonstrates that using the Architecture Analysis and Design Language (AADL) early in the development process not only helps detect design errors before implementation but also supports implementation efforts and produces high-quality code. Previous research has demonstrated how AADL can identify potential design errors and avoid propagating them through the development process. Verified specifications, however, are still implemented manually. This manual process is labor intensive and error prone, and it introduces errors that might break previously verified assumptions and requirements. For these reasons, code production should be automated to preserve system specifications throughout the development process. In this podcast, Julien Delange summarizes different perspectives on research related to code generation from software architecture models.