A Metascience Study of the Low-Code Scientific Field

Fuente: arXiv
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Main Authors: Tosi, Mauro Dalle Lucca, Izquierdo, Javier Luis Cánovas, Cabot, Jordi
Format: Preprint
Published: 2024
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author Tosi, Mauro Dalle Lucca
Izquierdo, Javier Luis Cánovas
Cabot, Jordi
author_facet Tosi, Mauro Dalle Lucca
Izquierdo, Javier Luis Cánovas
Cabot, Jordi
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2408_05975
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle A Metascience Study of the Low-Code Scientific Field
Tosi, Mauro Dalle Lucca
Izquierdo, Javier Luis Cánovas
Cabot, Jordi
Software Engineering
Digital Libraries
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.
title A Metascience Study of the Low-Code Scientific Field
topic Software Engineering
Digital Libraries
url https://arxiv.org/abs/2408.05975