We automate the creation of performance models out of standard design models. Such performance models can be automatically solved to evaluate performance aspects early in the development process
Overcome the limitations of executing model transformations on large models by distributing them on top of a mapreduce infrastructure. We’ve done it for ATL. Read the full details on this paper accepted in the Journal of Systems and Software
IDEs for model transformation languages are still rudimentary compared to IDEs of languages like Java o C. AnATLyzer has been created to fill this gap and provide some advanced IDE features for ATL.
Gremlin-ATL is a scalable and efficient model-to-model transformation framework that translates ATL transformations into Gremlin, a query language supported by several NoSQL databases
Looking for an alternative to the “standard” Java-based Eclipse Modeling Framework? Try this Python implementation of EMF with an emphasis on modeling flexibility and scripting (e.g. to write model transformations)
Read on to learn how formalizing model transformations and traceability mappings helps to chain, reuse and compose model transformations