Clustering of model instances by using graph kernels. Make sure you test your models with the most diverse set of examples!
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.
We present a conceptual reference framework to identify the foundations for intelligent modeling assistance as well as the open challenges and the opportunities they bring to the modeling world.
Our new Chabot DSL, based on state machine semantics, facilitates the creation of bots with complex conversational flows and maximizes the reuse of bot parts in future projects