Managing Belief Uncertainty in Models
We show how domain experts can individually reason about their models and combine their opinions to reach a consensus on the models and objects they are modeling
The impact of introducing a modeling tool in a Requirement Engineering course
In numerous programming and software engineering courses, students are asked to program on paper, which has supporters and detractors. Supporters claim that, among its advantages, programming on paper allows students to focus on functionality, avoiding the...
A Generic LSTM-Based Neural Network Architecture to infer Heterogeneous Model Transformations
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.
An NLP-based architecture for the autocompletion of partial domain models
Domain models capture the key concepts and relationships of a business domain, leaving out superfluous details. During the domain modeling activity carried out as part of a software development project, informal descriptions of a domain are translated into a...
Opportunities in Intelligent Modeling Assistance
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.
Modeling: all you need to know
