An Automated Technique for Analysis of Orthogonal Variability Models based on Anti-patterns Detection using DL reasoning

dc.creatorOyarzun, Ángela
dc.creatorBraun, Germán
dc.creatorCecchi, Laura
dc.creatorFillottrani, Pablo Rubén
dc.date2019-10
dc.date2019
dc.date2020-03-19T12:38:38Z
dc.date.accessioned2023-07-14T19:00:44Z
dc.date.available2023-07-14T19:00:44Z
dc.identifierhttp://sedici.unlp.edu.ar/handle/10915/91150
dc.identifierisbn:978-987-688-377-1
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/7433649
dc.descriptionDuring a Software Product Line (SPL) variability management, model validation is crucial so as to detect faults in early development stages and avoid affecting derived products quality. Therefore, the automated variability analysis has emerged for translating and validating variability models. In this work, we present a catalogue of anti-patterns, which describes scenarios associated to the detection of problems in a SPL. Moreover, we extend crowd-variability, a novel graphical tool designed for modelling and validating Orthogonal Variability Models (OVM), for detecting such anti-patterns using Description Logics (DL)-based reasoning services.
dc.descriptionXI Workshop Innovación en Sistemas de Software.
dc.descriptionRed de Universidades con Carreras en Informática
dc.formatapplication/pdf
dc.format940-949
dc.languageen
dc.rightshttp://creativecommons.org/licenses/by-nc-sa/4.0/
dc.rightsCreative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.subjectCiencias Informáticas
dc.subjectSoftware product lines
dc.subjectOrthogonal Variability Models
dc.subjectDescription logics
dc.subjectGraphical tools for modelling variability
dc.titleAn Automated Technique for Analysis of Orthogonal Variability Models based on Anti-patterns Detection using DL reasoning
dc.typeObjeto de conferencia
dc.typeObjeto de conferencia


Este ítem pertenece a la siguiente institución