Is there a future for Model Transformation Languages?
Model transformations and manipulations are a key element in any model-driven engineering approach. The “traditional” way to tackle model transformation problems is to write a transformation program using a specific transformation language (such as ATL, QVT, ETL, …).
But this traditional strategy seems to lead us nowhere. On the one hand, many companies prefer to write transformations directly in general languages like Java. On the other hand, AI-based approaches could “simply” learn the transformations themselves by looking at pairs of <input, output> models.
The goal of this panel is to discuss whether there is still a future for Transformation Languages. If not, what will replace them?. If yes, how can they remain relevant? Come to see if we kill them all or they will keep reigning for another decade.
Do you have a strong opinion / interesting perspective on this? Contact Jordi.email@example.com until end of May!