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21.06.2022 | Regular Paper

Blended modeling in commercial and open-source model-driven software engineering tools: A systematic study

verfasst von: Istvan David, Malvina Latifaj, Jakob Pietron, Weixing Zhang, Federico Ciccozzi, Ivano Malavolta, Alexander Raschke, Jan-Philipp Steghöfer, Regina Hebig

Erschienen in: Software and Systems Modeling | Ausgabe 1/2023

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Abstract

Blended modeling aims to improve the user experience of modeling activities by prioritizing the seamless interaction with models through multiple notations over the consistency of the models. Inconsistency tolerance, thus, becomes an important aspect in such settings. To understand the potential of current commercial and open-source modeling tools to support blended modeling, we have designed and carried out a systematic study. We identify challenges and opportunities in the tooling aspect of blended modeling. Specifically, we investigate the user-facing and implementation-related characteristics of existing modeling tools that already support multiple types of notations and map their support for other blended aspects, such as inconsistency tolerance, and elevated user experience. For the sake of completeness, we have conducted a multivocal study, encompassing an academic review, and grey literature review. We have reviewed nearly 5000 academic papers and nearly 1500 entries of grey literature. We have identified 133 candidate tools, and eventually selected 26 of them to represent the current spectrum of modeling tools.

Vorheriger Artikel Empirical analysis of the tool support for software product lines

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The identifiers used in this section are consistent with those used in the replication package to enable better traceability.

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Titel: Blended modeling in commercial and open-source model-driven software engineering tools: A systematic study
verfasst von: Istvan David
Malvina Latifaj
Jakob Pietron
Weixing Zhang
Federico Ciccozzi
Ivano Malavolta
Alexander Raschke
Jan-Philipp Steghöfer
Regina Hebig
Publikationsdatum: 21.06.2022
Verlag: Springer Berlin Heidelberg
Erschienen in: Software and Systems Modeling / Ausgabe 1/2023
Print ISSN: 1619-1366
Elektronische ISSN: 1619-1374
DOI: https://doi.org/10.1007/s10270-022-01010-3

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