🤖 AI Summary
This work addresses the lack of end-to-end traceability from high-level models to generated code in Model-Driven Engineering (MDE) by proposing the ProMoTA framework. ProMoTA unifies the entire modeling and code generation process—spanning platform-independent models, platform-specific models, and final code—through megamodels and model transformation chains. The framework innovatively extends the Acceleo language to support fine-grained local traceability and, for the first time, enables comprehensive global traceability mapping and analysis across the full MDE lifecycle. Implemented on the Eclipse platform, ProMoTA’s effectiveness in facilitating end-to-end traceability analysis is empirically validated through a case study in wireless sensor network-based Internet of Things applications.
📝 Abstract
In this paper, we propose an approach that integrates end-to-end traceability with process modelling. OurprocessmodelsrepresentMDEworkflowsthatspan platform-independent-modelling, platform-specificmodelling, andcodegenerationphases. Processexecutionisautomated using megamodels and model transformation chains. The generation of end-to-end traceability information enables global model traceability, from high-level input models to generated code, forming the basis for traceability analysis. We have built an Eclipse-based framework, ProMoTA, to support our approach. ProMoTA extends the Acceleo model transformation language, introducing local traceability support. It also includes a global traceability map generator and end-to-end traceability analysis modules, providing users with a holistic view of the entire transformation process. Our framework is demonstrated with the use of a Wireless Sensor Network-Based IoT application.