In space industry, model-driven engineering (MDE) is a key technique to model data exchanges with satellites. During the preparation of a space mission, the associated data models are often revised and need to be compared from one version to another. Thus, due to the undeniably growth of changes, it becomes difficult to track them. New methods and techniques to understand and represent the differences, as well as commonalities, between different model's revisions are highly required. Recent research works address the evolution process between the two layers (M2/M1) of the MDE architecture. In this research work, we have explored the use of the layers (M1/M0) of the same architecture in order to define a set of atomic operators and their composition that encapsulate both data model evolution and data migration. The use of these operators improves the quality of data migration, by ensuring full conservation of the information carried by the data.
Open Archive Toulouse Archive OuverteOATAO is an open access repository that collects the work of Toulouse researchers and makes it freely available over the web where possible a b s t r a c t During the development of a complex system, data models are the key to a successful engineering process, as they contain and organize all the information manipulated by the different functions involved in the design of the system. Moreover, these data models evolve throughout the design, as the development raises issues that have to be solved through a restructuration of data organization. But any such data model evolution has a deep impact on the functions that have already being defined.Recent research tries to deal with this issue by studying how complex industrial data models evolve from one version to another and how their data instances co-evolve. Complexity and scalability issues make this problem a major scientific challenge, leading to huge gains in development efficiency. This problem is of particular interest in the field of aeronautics and space systems. Indeed, the development of these systems produces many complex data models associated to the designed systems and/or to the systems under design, hence on the one hand data models are available. On the other hand, it is well known that these systems are developed in the context of collaborative projects that may last for decades. In such projects, specifications together with the associated data models are bound to evolve and engineering processes shall take into account this evolution.Our work addresses the problem of data model evolution in a model-driven engineering setting. We focus on minimizing the impact of model evolution on the system development processes in the specific context on the space engineering area, where data models may involve thousands of concepts and relationships, and we investigate the performance of the model-based development (MBD) approach we propose for data model evolution over two space missions, namely PHARAO and MICROSCOPE.
Nowadays, in the world of industry end-users of business rules inside huge or small companies claims that it's so hard to understand the rules either because they are hand written by a specific structural or procedural languages used only inside their organizations or because they require a certain understanding of the back-end process. As a result, a high need for a better management system that is easy to use, easy to maintain during the evolution process has increased. In this paper, the emphasis is put on building a business rule management system (BRMS) as a graphical editor for editing the models in a flexible agile manner with the assistant of ATL and Sirius frameworks within Eclipse platform. Thus, the proposed solution, on one hand, solves the problem of wasting resources dedicated for updating the rules and on the other hand it guarantees a great visibility and reusability of the rules.
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