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Towards LLM-powered consistency in model-based low-code platforms

Hagel, Nathan ORCID iD icon 1; Hili, Nicolas; Bartel, Alexander; Koziolek, Anne ORCID iD icon 1
1 Institut für Informationssicherheit und Verlässlichkeit (KASTEL), Karlsruher Institut für Technologie (KIT)

Abstract:

Low-code platforms often use various models that define the application built by citizen developers.
With the increasing size and complexity of the applications built using low-code platforms, the number of required models and the dependencies between them expand.
However, with increased complexity, keeping these models consistent during the development or evolution of the application is crucial and often a non-trivial task for citizen developers.
In this paper, we present four approaches to how LLMs can be used and integrated on the architecture level into low-code platforms to (i) create consistent models automatically, (ii) keep models consistent based on different types of dependencies, and (iii) support users in maintaining consistent models during the development.
We implemented the approaches in a prototype and evaluated them in an exploratory study.
The results show that state-of-the-art LLMs are capable of preserving consistency for low-code models as well as generating correct and consistent models in various scenarios.


Postprint §
DOI: 10.5445/IR/1000180779
Veröffentlicht am 07.04.2025
Originalveröffentlichung
DOI: 10.1109/ICSA-C65153.2025.00058
Scopus
Zitationen: 1
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Informationssicherheit und Verlässlichkeit (KASTEL)
Publikationstyp Proceedingsbeitrag
Publikationsdatum 05.04.2025
Sprache Englisch
Identifikator ISBN: 979-8-3315-3337-3
KITopen-ID: 1000180779
HGF-Programm 46.23.01 (POF IV, LK 01) Methods for Engineering Secure Systems
Erschienen in 2025 IEEE 22nd International Conference on Software Architecture Companion (ICSA-C)
Veranstaltung 22nd IEEE International Conference on Software Architecture Companion (ICSA-C 2025), Ottensee, Dänemark, 31.03.2025 – 04.04.2025
Verlag Institute of Electrical and Electronics Engineers (IEEE)
Seiten 364-369
Projektinformation SFB 1608/1, 501798263 (DFG, DFG KOORD, SFB 1608)
Bemerkung zur Veröffentlichung in press
Schlagwörter LLM, AI, low-code development platform, meta-model, model-driven engineering, DSL, consistency
Nachgewiesen in Scopus
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