Towards the next generation of reactive model transformations on low-code platforms: Three research lines

Abstract

Low-Code Development Platforms have emerged as the next-generation, cloud-enabled collaborative platforms. These platforms adopt the principles of Model-Driven Engineering, where models are used as first-class citizens to build complex systems, and model transformations are employed to keep a consistent view between the different aspects of them. Due to the online nature of low-code platforms, users expect them to be responsive, to complete complex operations in a short time. To support such complex collaboration scenarios, the next-generation of low-code platforms must (i) offer a multi-tenant environment to manage the collaborative work of engineers, (ii) provide a model processing paradigm scaling up to hundreds of millions of elements, and (iii) provide engineers a set of selection criteria to choose the right model transformation engine in multi-tenant execution environments. In this paper, we outline three research lines to improve the performance of reactive model transformations on low-code platforms, by motivating our research with a case study from a systems engineering domain.