
Social diversity in the automatic learning of complex MDE artefacts
Learn how genetic programming, enhanced by a new social diversity measure, can automatically learn complex models
Learn how genetic programming, enhanced by a new social diversity measure, can automatically learn complex models
Existing software languages do not capitalize on monitored usage data of the language and its modeling environment. This hinders the continuous and automatic evolution of the software language based on feedback loops.
Model powerful security policies for your software designs with our DSL based on the UCON usage control model
Clustering of model instances by using graph kernels. Make sure you test your models with the most diverse set of examples!
We propose an iterative modeling approach where designers can dynamically customize the level of formality required in each iteration in a visual and intuitive way
PAMELA proposes a shift in the modeling paradigm, in which models and code are developed together and at the same time in what we call a continuous modeling process.