Abstract
Low-Code Development Platforms (LCDPs) are software development platforms on the Cloud, provided through a Platform-as-a-Service model, which allow users to build completely operational applications by interacting through dynamic graphical user interfaces, visual diagrams and declarative languages. Lowcomote will train a generation of experts that will upgrade the current trend of LCDP to a new paradigm, Low-Code Engineering Platform. This will be achieved by injecting in LCDPs the theoretical and technical framework defined by recent research in Model Driven Engineering, augmented with Cloud Computing and Machine Learning techniques.
| Original language | English |
|---|---|
| Journal | CEUR Workshop Proceedings |
| Volume | 2405 |
| Publication status | Published - 2019 |
| Event | Software Technologies: Applications and Foundations, STAF 2019 - Co-located Joint Events: 1st Junior Researcher Community Event, 2nd International Workshop on Model-Driven Engineering for Design-Runtime Interaction in Complex Systems, and 1st Research Project Showcase Workshop - Eindhoven, Netherlands Duration: 15 Jul 2019 → 19 Jul 2019 |
Bibliographical note
Funding Information:In this paper we have provided an outline of the main challenges of Low-Code Engineering and how the Lowcomote ITN will address them. The technical outcome will be a set of components of a single open platform named Lowcomotive. It will be a platform as a service, based on open standards at all levels (e.g., EMF, language-server-protocol, OpenStack). A frontend will provide LCE languages and smart interfaces that end-users will exploit to produce their artefacts. A backend will come in the form of a LCE repository providing server-side services for LCE developers. Industrial partners will provide case studies to ESRs develop and run their experiments. Acknowlegments. This project has received funding from the EU Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 813884.
Funding Information:
This project has received funding from the EU Horizon 2020 research and innovation programme under the Marie Sk?odowska-Curie grant agreement No 813884.
Publisher Copyright:
Copyright © 2019 for this paper by its authors.