Quantum computing is getting closer and closer to being embedded in commercial information systems. This post shows you how to modernize, via a KDM to UML transformation, “traditional systems” and them ready to become hybrid systems embedding quantum software components
We propose to take advantage of the advances in Artificial Intelligence and, in particular, Long Short-Term Memory Neural Networks (LSTM), to automatically infer heterogeneous model transformations from sets of input-output model pairs.
Are you using model transformation languages to manipulate your models? If not, why? Should we just get rid of all transformation languages and use plain Java?. Participate in this discussion about the future of model transformations.
Summary of our contributions towards a scalable query and transformation modeling framework able to handle very large models
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
