We seek to increase user confidence in simulations as they are adapted to meet new requirements. Our approach includes formal representation of uncertainty, lightweight validation,...
Paul F. Reynolds Jr., Michael Spiegel, Xinyu Liu, ...
During the development of car engines, regression models that are based on machine learning techniques are increasingly important for tasks which require a prediction of results i...
A software development process is conceptually an abstract form of model transformation, starting from an enduser model of requirements, through to a system model for which code c...
Emine G. Aydal, Richard F. Paige, Mark Utting, Jim...
In this paper we propose a method to derive OCL invariants from declarative model-to-model transformations in order to enable their verification and analysis. For this purpose we ...