Please use this identifier to cite or link to this item: https://repositorio.usj.es/handle/123456789/776

Title: Comprehensibility of Variability in Model Fragments for Product Configuration
Authors: Echeverría Ochoa, Jorge
Cetina, Carlos ORCID RESEARCHERID SCOPUSID
Pérez, Francisca ORCID SCOPUSID
Pastor Lopez, Oscar ORCID RESEARCHERID SCOPUSID
Keywords: Variability modeling; Software product line engineering; Model comprehension; Product configuration
Issue Date: 2016
Publisher: Springer
Citation: Echeverría, J., Pérez, F., Cetina, C., Pastor, Ó. (2016). Comprehensibility of Variability in Model Fragments for Product Configuration. In: Nurcan, S., Soffer, P., Bajec, M., Eder, J. (eds) Advanced Information Systems Engineering. CAiSE 2016. Lecture Notes in Computer Science(), vol 9694. Springer, Cham. https://doi.org/10.1007/978-3-319-39696-5_29
Abstract: The ability to manage variability in software has become crucial to overcome the complexity and variety of systems. To this end, a comprehensible representation of variability is important. Nevertheless, in previous works, difficulties have been detected to understand variability in an industrial environment. Specifically, domain experts had difficulty understanding variability in model fragments to produce the software for their products. Hence, the aim of this paper is to further investigate these difficulties by conducting an experiment in which participants deal with variability in order to achieve their desired product configurations. Our results show new insights into product configuration which suggest next steps to improve general variability modeling approaches, and therefore promoting the adoption of these approaches in industry.
URI: https://repositorio.usj.es/handle/123456789/776
Appears in Collections:Comunicaciones a congresos, conferencias

Files in This Item:
File Description SizeFormat 
Echeverría2016_Chapter_ComprehensibilityOfVariability (1).pdf615,75 kBAdobe PDFThumbnail
View/Open


This item is licensed under a Creative Commons License Creative Commons