Efficient model partitioning for distributed model transformations
Amine Benelallam, Massimo Tisi, Jesús Sánchez Cuadrado, Juan D. Lara, Jordi Cabot · 2016
As the models that need to be handled in model-driven engineering grow in scale, scalable algorithms for model transformation (MT) are becoming necessary. Programming models such as MapReduce or Pregel may simplify the development of distributed model transformations. However, because of the dense inter-connectivity of models and the complexity of transformation logics, scalability in distributed model processing is challenging.