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

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

*Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review

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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.

Original languageEnglish
Pages (from-to)415-447
Number of pages33
JournalSoftware and Systems Modeling
Volume22
Issue number1
Early online date21 Jun 2022
DOIs
Publication statusPublished - Feb 2023

Bibliographical note

Funding Information:
This research was partially funded by the Rijksdienst voor Ondernemend Nederland (RVO) through the ITEA3 BUMBLE project (18006)

Publisher Copyright:
© 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

Funding

This research was partially funded by the Rijksdienst voor Ondernemend Nederland (RVO) through the ITEA3 BUMBLE project (18006)

Keywords

  • Inconsistency tolerance
  • Model-driven development
  • Modeling tools
  • Multi-view modeling
  • Survey

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