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The increasing need for continuously available softwaresystems has raised two key-issues: self-adaptation anddesign evolution. The former one requires software systems to monitor their execution platform and automatically adapt their configuration and/or architecture to adjust their quality of service (optimization, fault-handling). The later one requires(More)
In the landscape of cloud computing, the competition between providers has led to an ever growing number of cloud solutions offered to consumers. The ability to run and manage multi-cloud systems (i.e., applications on multiple clouds) allows exploiting the peculiarities of each cloud solution and hence optimising the performance, availability, and cost of(More)
The market of cloud computing encompasses an ever-growing number of cloud providers offering a multitude of infrastructure-as-a-service (IaaS) and platform-as-a-service (PaaS) solutions. The heterogeneity of these solutions hinders the proper exploitation of cloud computing since it prevents interoperability and promotes vendor lock-in, which increases the(More)
Dynamically adaptive systems (DAS) enable the continuous design and adaptation of complex software systems, but their main focus is limited to the application itself rather than the underlying platform and infrastructure. Cloud computing, in contrast, enables the management of the complete software stack, but it lacks integration with software engineering(More)
Les plates-formes d'exécution récentes telles que Fractal ou Open-COM offrent de nombreuses facilités pour assurer la prise en compte de pro-priétés extra-fonctionnelles (introspection, sondes, chargement dynamique, etc). Cependant, l'intégration de politiques d'adaptation reste délicate car elle néces-site de corréler la configuration du système avec(More)
The key point to leverage model-based techniques on runtime system management is to ensure the correct synchronization between the running system and its model-based view. In this paper, we present a generative approach, and the supporting tool, to make systematic the development of synchronization engines between running systems and models. We require(More)
UML semantic variation points provide intentional degrees of freedom for the interpretation of the metamodel semantics. The interest of semantic variation points is that UML now becomes a family of languages sharing lot of commonalities and some variabilities that one can customize for a given application domain. In this paper, we propose to reify the(More)