Supporting changes in software models is becoming increasingly important. Some of these changes are induced by non-functional analysis that is usually conducted on different models and tools. Therefore, it becomes crucial to develop methods that allow automated transformations between these two families of models throughout the development cycle. To this extent, in the last decade, a number of approaches have been introduced to generate nonfunctional analysis models from software models. However, when analysis models are modified to meet non-functional requirements, changes are not propagated to update the software model. Automating the identification and propagation of changes would better support a round-trip analysis process. In this PhD program, we aim at introducing automation in the model-driven assessment of dependability, and we propose to leverage bidirectional model transformations to: (i) generate dependability analysis models from software models, and (ii) automatically propagate changes, driven by dependability requirements satisfaction, from analysis models back to software models. In particular, we intend to extend JTL, that is a bidirectional model transformations framework designed for model synchronization and change propagation, to handle problems that may arise from the application of bidirectional transformations in the context of dependability assessment.
|Titolo:||Model-driven round-trip software dependability engineering|
|Data di pubblicazione:||2018|
|Appare nelle tipologie:||4.1 Contributo in Atti di convegno|