Turning Low-Code Development Platforms into True No-Code with LLMs
The relevance of low-code / no-code development has grown substantially in research and practice over the years to allow nontechnical users to create applications and, therefore, democratise software development. One problem in this domain still persists: many platforms remain low-code as the underlying modeling layer still requires professionals to write/design a model, often using Domain Specific Languages (DSLs). With the rise of generative AI and Large Language Models (LLMs) and their capabilities, new possibilities emerge on how Low Code Development Platforms (LCDPs) can be improved.
Authors
- Didier Schwab (ORCID: https://orcid.org/0000-0002-2462-8148)
- Nicolas Hili (ORCID: https://orcid.org/0000-0003-3044-3745)
- Nathan Hagel (ORCID: https://orcid.org/0009-0003-9919-4449)
Institutions
- Karlsruhe Institute of Technology (DE)
- Institut polytechnique de Grenoble (FR)
- Laboratoire d'Informatique de Grenoble (FR)
- Université Grenoble Alpes (FR)
Publication Details
- Published
- 2024-09-22
- DOI
- https://doi.org/10.1145/3652620.3688334
- Citations
- 12
- Primary Topic
- Software Testing and Debugging Techniques
- Type
- article
- Field-Weighted Citation Impact
- 5.83
Funders
- Agence Nationale de la Recherche