ESR 2: Scalable Cloud-Based Heterogeneous Modelling
LCDPs typically allow describing different aspects of an application using graphical models. When the targeted application is complex or encompasses many concepts, their models become large and, without appropriate tool support, they get difficult to create, reuse, navigate, and comprehend. There are a few domain-specific modelling frameworks for web-based editing, some of them developed by our consortium. However, the reality is that creating web-based graphical editors with existing frameworks is still hard and time-consuming due to their low-level code nature. Moreover, the created editors are not scalable beyond tens of elements, are tied to a modelling technology, do not enable rich modelling of editor aspects (e.g., domain-specific abstractions), or do not connect different languages through views.
As use cases, we will use the framework to build editors for low-code platforms – including ROSE – but also to monitor and abstract the logs of the applications generated with them, which for some applications may contain hundred millions of registered transactions.
The result of the project will be a framework to create Cloud-based modelling environments supporting abstraction, multi-view and heterogeneous modelling platforms. The framework will be based on language engineering techniques.
We target to at least 50% time reduction for building editors (compared to manual coding), while the abstraction techniques on Cloud will be able to handle models with millions of elements.
Please note that the vacancy on the institutionnal website must be considered as the official version of this PhD position.
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