Cloud computing is emerging as a major trend in the ICT industry. While most of the attention of the research community is focused on considering the perspective of the Cloud providers, offering mechanisms to support scaling of resources and interoperability and federation between Clouds, the perspective of developers and operators willing to choose the Cloud without being strictly bound to a specific solution is mostly neglected. We argue that Model-Driven Development can be helpful in this context as it would allow developers to design software systems in a cloud-agnostic way and to be supported by model transformation techniques into the process of instantiating the system into specific, possibly, multiple Clouds. The MODA-CLOUDS (MOdel-Driven Approach for the design and execution of applications on multiple Clouds) approach we present here is based on these principles and aims at supporting system developers and operators in exploiting multiple Clouds for the same system and in migrating (part of) their systems from Cloud to Cloud as needed. MODACLOUDS offers a qualitydriven design, development and operation method and features a Decision Support System to enable risk analysis for the selection of Cloud providers and for the evaluation of the Cloud adoption impact on internal business processes. Furthermore, MODACLOUDS offers a run-time environment for observing the system under execution and for enabling a feedback loop with the design environment. This allows system developers to react to performance fluctuations and to redeploy applications on different Clouds on the long term.

1. 40% des investissements dans les technologies de l'information sont utilisés juste pour l'intégration des différentes technologies utilisées un sein d'un même système [7]. 2. La littérature anglo-saxonne qualifie ces propriétés de « self-star » ou « self-* » [9].

Abstract. One of the main goals of model-driven engineering is the manipulation of models as exclusive software artifacts. Model execution is in particular a means to substitute models for code. We focus in this paper on verifying model executions. We use a contract-based approach to specify an execution semantics for a meta-model. We show that an execution semantics is a seamless extension of a rigorous meta-model specification and is composed of complementary levels, from static element definition to dynamic elements, execution specifications as well. We use model transformation contracts for controlling the dynamic consistent evolution of a model during its execution. As an illustration, we apply our approach to UML state machines using OCL as the contract expression language.

No abstract