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A Metascience Study of the Low-Code Scientific Field

2024/08/12 by Mauro Dalle Lucca Tosi, Tosi, Mauro Dalle Lucca, Javier Luis Izquierdo +3
Computer Science · Psychology · #Digital Libraries (cs.DL) #Educational Games and Gamification #FOS: Computer and information sciences #Intelligent Tutoring Systems and Adaptive Learning #Model-Driven Software Engineering Techniques #Software Engineering (cs.SE)

paper · pdf · doi:10.48550/arxiv.2408.05975

openalex publication_date 2024/08/12 · openalex created_date 2024/09/10 · openalex updated_date 2026/07/28

Abstract

In the last years, model-related publications have been exploring the application of modeling techniques across various domains. Initially focused on UML and the Model-Driven Architecture approach, the literature has been evolving towards the usage of more general concepts such as Model-Driven Development or Model-Driven Engineering. More recently, however, the term "low-code" has taken the modeling field by storm, largely due to its association with several highly popular development platforms. The research community is still discussing the differences and commonalities between this emerging term and previous modeling-related concepts, as well as the broader implications of low-code on the modeling field. In this paper, we present a metascience study of Low-Code. Our study follows a two-fold approach: (1) to analyze the composition and growth (e.g., size, diversity, venues, and topics) of the emerging Low-Code community; and (2) to explore how these aspects differ from those of the "classical" model-driven community. Ultimately, we hope to trigger a discussion on the current state and potential future trajectory of the low-code community, as well as the opportunities for collaboration and synergies between the low-code and modeling communities.

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