MUNANTE, Denisse; KIFETEW, Fitsum Meshesha; GORRONOGOITIA, Jesus; SCHANIEL, Ronnie; PERINI, Anna; SUSI, Angelo

doi:10.1109/MoDRE.2018.00009

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MUNANTE, Denisse
ESTIA INSTITUTE OF TECHNOLOGY

KIFETEW, Fitsum Meshesha

GORRONOGOITIA, Jesus

Langue

Communication dans un congrès

Ce document a été publié dans

8th IEEE International Model-Driven Requirements Engineering Workshop, MoDRE@RE 2018, Banff, AB, Canada, 8th International Model-Driven Requirements Engineering Workshop (MoDRE), 2018-08-20, Banff. n° ISBN 978-1-5386-8406-1, p. 21-25

IEEE

Résumé en anglais

Dynamic reconfiguration of software systems can be achieved by exploiting variability models of such systems, combined with mechanisms for selecting and instantiating the appropriate system configuration. We developed a model-driven approach for dynamic software reconfiguration, which uses a component profile-oriented feature model for representing different configurations of a software system, and a grammar based genetic programming tool that, at run-time, automatically generates an optimal system configuration. The resulting feature configuration is transformed to a target format such as JSON, SQL or other specification that allows us to instantiate the new system configuration. In this paper we focus on the run-time reasoning and propagation aspect, and discuss our experience on applying the approach to a use case.< Réduire

Mots clés en anglais

Genetic programming

Feature model

models@runtime

URI

https://oskar-bordeaux.fr/handle/20.500.12278/200352

DOI

http://dx.doi.org/10.1109/MoDRE.2018.00009

Projet Européen

SUpporting evolution and adaptation of PERsonalized Software by Exploiting contextual Data and End-user feedback

Unités de recherche

ESTIA - Recherche