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 ![]() ![]() ![]() Pérez Pérez, Francisca ![]() ![]() Pastor Lopez, Oscar ![]() ![]() ![]() |
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 | Size | Format | |
---|---|---|---|---|
Echeverría2016_Chapter_ComprehensibilityOfVariability (1).pdf | 615,75 kB | Adobe PDF | ![]() View/Open |
This item is licensed under a Creative Commons License