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1 Laboratoire d-Informatique, Signaux, et Systèmes de Sophia-Antipolis I3S - Equipe MODALIS SPARKS - Scalable and Pervasive softwARe and Knowledge Systems 2 SINTEF - Stiftelsen for INdustriell og TEknisk Forskning 3 PULSAR - Perception Understanding Learning Systems for Activity Recognition CRISAM - Inria Sophia Antipolis - Méditerranée

Abstract : Self-adaptive and dynamic systems adapt their behavior according to the context of execution. The contextual information exhibits multiple variability factors which induce many possible configurations of the software system at runtime. The challenge is to specify the adaptation rules that can link the dynamic variability of the context with the possible variants of the system. Our work investigates the systematic use of feature models for modeling the context and the software variants, together with their inter relations, as a way to configure the adaptive system with respect to a particular context. A case study in the domain of video surveillance systems is used to illustrate the approach.

Author: Mathieu Acher - Philippe Collet - Franck Fleurey - Philippe Lahire - Sabine Moisan - Jean-Paul Rigault -



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