RT Journal Article
T1 Probabilistic software product lines
A1 Camacho, Carlos
A1 Llana Díaz, Luis Fernando
A1 Núñez Covarrubias, Alberto
A1 Bravetti, Mario
AB We introduce a probabilistic extension of our previous work SPLA: a formal framework to specify and analyze software product lines. We use probabilistic information to identify those features that are more frequently used. This is done by computing the probability of having a feature in a specific software product line, from now on SPLAP . We redefine the syntax of SPLA to include probabilistic operators and define new operational and denotational semantics. We prove that the expected equivalence between these two semantic frameworks holds. Our probabilistic framework is supported by a set of scripts to show the model behavior. We briefly comment on the characteristics of the scripts and discuss the advantages of using probabilities to quantify the likelihood of having features in potential software product lines.
PB Elsevier
SN 2352-2208
YR 2019
FD 2019-10
LK https://hdl.handle.net/20.500.14352/112911
UL https://hdl.handle.net/20.500.14352/112911
LA eng
NO Camacho, Carlos, et al. “Probabilistic Software Product Lines”. Journal of Logical and Algebraic Methods in Programming, vol. 107, octubre de 2019, pp. 54–78, https://doi.org/10.1016/j.jlamp.2019.05.007
NO Ministerio de Economía y Competitividad (España)
NO Comunidad de Madrid
DS Docta Complutense
RD 7 abr 2025