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The technological landscape of collaborative model-driven software engineering
Vrije Univ Amsterdam, Amsterdam, Netherlands.
Vrije Univ Amsterdam, Amsterdam, Netherlands.
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems. Mälardalen Univ, Västerås, Sweden.ORCID iD: 0000-0002-0401-1036
Vrije Univ Amsterdam, Amsterdam, Netherlands.
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2025 (English)In: Software and Systems Modeling, ISSN 1619-1366, E-ISSN 1619-1374Article in journal (Refereed) Published
Abstract [en]

Collaborative technologies are continuously evolving to address existing problems and introduce innovative features for enhancing collaboration in the landscape of model-driven software engineering (MDSE). Different collaborative MDSE technologies (CMTs) provide different solutions to facilitate collaboration, making it hard for practitioners to choose the technology that best suits their needs. This study aims to investigate the landscape of CMTs and to provide a list of recommended technologies tailored to specific use case scenarios in the context of MDSE. We compiled a comprehensive list of CMTs using a systematic search complemented with snowballing, investigating both academic and grey literature. The technologies were selected through a set of inclusion and exclusion criteria and eventually analyzed through an in-depth analysis focusing on model management, collaboration, and communication. The findings of our study reveal that the current landscape of CMTs is characterized by a relatively narrow range of capabilities offered by different technologies. Consequently, practitioners often have to become proficient in combining several different technologies in order to meet their needs. While various CMTs offer distinct collaboration approaches, the current landscape could be richer in terms of capabilities. Our research provides a comprehensive description of recommended CMTs, enabling practitioners to make informed decisions and improve collaboration in their MDSE processes.

Place, publisher, year, edition, pages
Springer Nature , 2025.
Keywords [en]
Collaborative modeling, Model-driven software engineering, Collaborative modeling technologies
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:mdh:diva-70555DOI: 10.1007/s10270-025-01274-5ISI: 001431115900001Scopus ID: 2-s2.0-105000009664OAI: oai:DiVA.org:mdh-70555DiVA, id: diva2:1948625
Available from: 2025-03-31 Created: 2025-03-31 Last updated: 2025-11-03Bibliographically approved

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Ciccozzi, Federico

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