Section: Contracts and Grants with Industry

MIA-Software research collaboration, Scalability of MDE techniques (2011-2012)

Since several years, AtlandMod and Mia-Software are actively collaborating around the topic of Model Driven Reverse Engineering (MDRE), i.e.; the combined use of different model-based techniques to solve real reverse engineering problems. This has resulted in the successful creation and development of two open source Eclipse projects, namely Eclipse-MDT MoDisco (providing a generic and extensible MDRE framework) and Eclipse-EMFT EMF Facet (providing a dynamic model extension framework), both reaching today an industrial maturity level.

However, for these technologies to be definitely adopted and deployed in the context of very large systems handling huge data volumes, some remaining scalability issues still have to be addressed. Thus, scalability of model-driven techniques is one of the main challenges MDE is facing right now. In this context, AtlanMod has joined forces with MIA-Software as part of an INRIA technology transfer action. This initiative is devoted to the development of new generation MDE techniques, for model creation and general handling, that effectively scale up.

Several of our projects are going to be positively impacted by the results produced during this collaboration, of course the MoDisco and EMF Facet frameworks as mentioned before, but also others such as notably the related ATL model transformation technology. Among the different research challenges behind the MDE scalability and performance improvement, the following ones are being or will be explored in the context of this collaborative action:

  • Model random access. Advanced use of on-demand lazy loading techniques;

  • Model clustering and slicing. Advanced use of semantic grouping and partial loading techniques;

  • Model virtualization. Transparent and on-demand access to different views on a same model;

  • Lazy evaluation of model transformation. On-demand lazy execution of transformations;

  • Incremental model transformation. Partial model access and transformation execution;

  • Multi-threaded model transformation. Parallelization of both model accesses and rule executions.

Officially started recently, this initiative has already opened very promising perspectives for the future in terms of both research and industrial opportunities (e.g.; regarding new national and international project proposals on innovative research topics of common interest).