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A generic LSTM neural network architecture to infer heterogeneous model transformations.
Models capture relevant properties of systems. During the models’ life-cycle, they are subjected to manipulations with different goals such as managing software evolution, performing analysis, increasing developers’ ... -
Belief Uncertainty in Software Models
Burgueño-Caballero, Lola; Clarisó, Robert; Cabot, Jordi; Gérard, Sébastien; Vallecillo-Moreno, Antonio Jesús (2020-06-08)This paper discusses the representation of Belief Uncertainty in software models. This kind of uncertainty refers to the situation in which the modeler, or any other belief agent, is uncertain about the behavior of the ... -
Combining OCL and Natural Language: a Call for a Community Effort
Cabot, Jordi; Delgado, David; Burgueño-Caballero, Lola (ACM, 2022-10)The growing popularity and availability of pretrained natural language models opens the door to many interesting applications combining natural language (NL) with software artefacts. A couple of examples are the generation ... -
Dealing with Belief Uncertainty in Domain Models
Burgueño-Caballero, Lola; Muñoz, Paula; Clarisó, Robert; Cabot, Jordi; Gérard, Sébastien; Vallecillo-Moreno, Antonio Jesús[et al.] (ACM, 2023)There are numerous domains in which information systems need to deal with uncertain information. These uncertainties may originate from different reasons such as vagueness, imprecision, incompleteness, or inconsistencies, ... -
Dealing with Belief Uncertainty in Domain Models.
Burgueño-Caballero, Lola; Muñoz Ariza, Paula; Clarisó, Robert; Cabot, Jordi; Gérard, Sébastien; Vallecillo-Moreno, Antonio Jesús[et al.] (2023)There are numerous domains in which information systems need to deal with uncertain information. These uncertainties may originate from different reasons such as vagueness, imprecision, incompleteness or inconsistencies; ...