Section: New Results
The increasing number of companies embracing MDE methods and tools have exceeded the limits of the current model-based technologies, presenting scalability issues while facing the growing complexity of their data. Since further research and development is imperative in order to maintain MDE techniques as relevant as they are in less complex contexts, we have focused our research in three axes, (i) scalable persistence solutions, (ii) scalable model transformation engines, and (iii) testing of large scale distributed systems.
In  , we lead the first open-set benchmark gathered from real-world cases to stress scalability issues in model transformation and query engines. This benchmark suite has been made public with a twofold goal: (i) to provide a reference benchmark suite to both the industry and the research community that can be used to compare and evaluate different technologies that may fulfill their needs; and (ii) to motivate the MDE community to be part of its development by allowing them to extend and contribute with additional cases not covered by the initial set.
On the other hand, we introduce Neo4EMF  , a NoSQL database persistence framework based on Neo4j (http://www.neo4j.org ). Neo4EMF provides light-weight on-demand loading and storage facilities for handling very large models. Additionally, we also show that Neo4EMF can handle the creation of very-large models without performing periodical saves manually.
In this paper  , we argue that fUML may be leveraged to address the well-known interoperability issue between tools from different modeling platforms. This is done by providing a common execution language and by abstracting modeling frameworks into generic actions that perform elementary operations on models. User models can not only benefit from a unified execution semantics, but also modeling tools can benefit too. As a proof of concept, we show  how it can be applied to model transformation engines, in particular ATL. To this end, an prototype compiler from ATL to fUML has been built.
In  , we present a model-based approach to define a dynamic oracle for checking global properties on distributed software. Our objective is to abstract relevant aspects of such systems into models by gathering data from different nodes and building a global view of the system, where properties are validated. These models are updated at runtime, by monitoring the corresponding distributed system. This process requires a distributed test architecture and tools for representing and validating global properties. To evaluate the ability of our approach, a real-scale experimental validation has been conducted.