Satisfaction, Restriction and Amalgamation of Constraints in the Framework of M-Adhesive Categories

Application conditions for rules and constraints for graphs are well-known in the theory of graph transformation and have been extended already to M-adhesive transformation systems. According to the literature we distinguish between two kinds of satisfaction for constraints, called general and initial satisfaction of constraints, where initial satisfaction is defined for constraints over an initial object of the base category. Unfortunately, the standard definition of general satisfaction is not compatible with negation in contrast to initial satisfaction. Based on the well-known restriction of objects along type morphisms, we study in this paper restriction and amalgamation of application conditions and constraints together with their solutions. In our main result, we show compatibility of initial satisfaction for positive constraints with restriction and amalgamation, while general satisfaction fails in general. Our main result is based on the compatibility of composition via pushouts with restriction, which is ensured by the horizontal van Kampen property in addition to the vertical one that is generally satisfied in M-adhesive categories.Comment: In Proceedings ACCAT 2012, arXiv:1208.430

A research roadmap towards achieving scalability in model driven engineering

International audienceAs Model-Driven Engineering (MDE) is increasingly applied to larger and more complex systems, the current generation of modelling and model management technologies are being pushed to their limits in terms of capacity and eciency. Additional research and development is imperative in order to enable MDE to remain relevant with industrial practice and to continue delivering its widely recognised productivity , quality, and maintainability benefits. Achieving scalabil-ity in modelling and MDE involves being able to construct large models and domain-specific languages in a systematic manner, enabling teams of modellers to construct and refine large models in a collaborative manner, advancing the state of the art in model querying and transformations tools so that they can cope with large models (of the scale of millions of model elements), and providing an infrastructure for ecient storage, indexing and retrieval of large models. This paper attempts to provide a research roadmap for these aspects of scalability in MDE and outline directions for work in this emerging research area

Towards Transparent Combination of Model Management Execution Strategies for Low-Code Development Platforms

International audienceLow-code development platforms are taking an important place in the model-driven engineering ecosystem, raising new challenges, among which transparent efficiency or scalability. Indeed, the increasing size of models leads to difficulties in interacting with them efficiently. To tackle this scalability issue, some tools are built upon specific computational strategies exploiting reactivity, or parallelism. However, their performances may vary depending on the specific nature of their usage. Choosing the most suitable computational strategy for a given usage is a difficult task which should be automated. Besides, the most efficient solutions may be obtained by the use of several strategies at the same time. is paper motivates the need for a transparent multi-strategy execution mode for model-management operations. We present an overview of the different computational strategies used in the model-driven engineering ecosystem, and use a running example to introduce the benefits of mixing strategies for performing a single computation. is example helps us present our design ideas for a multi-strategy model-management system. e code-related and DevOps challenges that emerged from this analysis are also presented