J. Troya, M. Wimmer, L. Burgueño, A. Vallecillo: Towards Approximate Model Transformations, Third Workshop on the Analysis of Model Transformations (AMT) @ MODELS, Valencia, Spain; 29.09.2014; in: Proceedings of the Third Workshop on the Analysis of Model Transformations (AMT) @ MODELS, CEUR, (2014), pages 44 - 53. pdf


As the size and complexity of models grow, there is a need to count onnovel mechanisms and tools for transforming them. This is required, e.g., when model transformations need to provide target models without having access to the complete source models or in really short time—as it happens, e.g., with streaming models—or with very large models for which the transformation algorithmsbecome too slow to be of practical use if the complete population of a model isinvestigated. In this paper we introduce Approximate Model Transformations, which aim at producing target models that are accurate enough to provide meaningful and useful results in an efficient way, but without having to be fully correct. So to speak,this kind of transformations treats accuracy for execution performance. In particular, we redefine the traditional OCL operators used to query models (e.g.,all Instances, select, collect, etc.) by adopting sampling techniques and analyse the accuracy of approximate model transformations results.