Resumen:
Model transformations dealing with very large models need to count on mechanisms and tools to be able to manage them. The usual approach to improve performance in these cases has focused on the use of concurrency and parallelization techniques, which aim at producing the correct output model(s). In this paper we present our initial approach to produce target models that are accurate enough to provide meaningful and useful results, in an efficient way, but without having to be fully correct. We introduce the concept of Approximate Model Transformations.