RT Journal Article
T1 Dealing with Belief Uncertainty in Domain Models
A1 Burgueño-Caballero, Lola
A1 Muñoz, Paula
A1 Clarisó, Robert
A1 Cabot, Jordi
A1 Gérard, Sébastien
A1 Vallecillo-Moreno, Antonio Jesús
K1 Software
K1 Toma de decisión
AB 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, and in many cases, they cannot be neglected. In this article, we are interested in representing and processing uncertain information in domain models, considering the stakeholders’ beliefs (opinions). We show how to associate beliefs to model elements and how to propagate and operate with their associated uncertainty so that domain experts can individually reason about their models enriched with their personal opinions. In addition, we address the challenge of combining the opinions of different domain experts on the same model elements, with the goal to come up with informed collective decisions. We provide different strategies and a methodology to optimally merge individual opinions.
PB ACM
YR 2023
FD 2023
LK https://hdl.handle.net/10630/30334
UL https://hdl.handle.net/10630/30334
LA eng
NO ACM Transactions on Software Engineering and MethodologyVolume 32Issue 2Article No.: 31pp 1–34 https://doi.org/10.1145/3542947
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 20 ene 2026