Repositorio de producción científica de la Universidad de Sevilla

Using Machine Learning to Infer Constraints for Product Lines

 

Advanced Search
 
Opened Access Using Machine Learning to Infer Constraints for Product Lines
Cites

Show item statistics
Icon
Export to
Author: Temple, Paul
Galindo Duarte, José Ángel
Acher, Mathieu
Jézéquel, Jean-Marc
Department: Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos
Date: 2016
Published in: SPLC 2016 : 20th International Systems and Software Product Line Conference (2016), p 209-218
Document type: Presentation
Abstract: Variability intensive systems may include several thousand features allowing for an enormous number of possible configurations, including wrong ones (e.g. the derived product does not compile). For years, engineers have been using constraints to...
[See more]
Cite: Temple, P., Galindo Duarte, J.Á., Acher, M. y Jézéquel, J. (2016). Using Machine Learning to Infer Constraints for Product Lines. En SPLC 2016 : 20th International Systems and Software Product Line Conference (209-218), Beijing, China: ACM.
Size: 1.629Mb
Format: PDF

URI: http://hdl.handle.net/11441/62946

DOI: 10.1145/2934466.2934472

See editor´s version

This work is under a Creative Commons License: 
Attribution-NonCommercial-NoDerivatives 4.0 Internacional

This item appears in the following Collection(s)