Predoaia, Ionut orcid.org/0000-0002-2009-4054 (2023) Towards Systematic Engineering of Hybrid Graphical-Textual Domain-Specific Languages. In: Proceedings - 2023 ACM/IEEE International Conference on Model Driven Engineering Languages and Systems Companion, MODELS-C 2023. 2023 ACM/IEEE International Conference on Model Driven Engineering Languages and Systems, MODELS-C 2023, 01-06 Oct 2023 IEEE , SWE , pp. 153-158.
Abstract
A domain-specific language (DSL) can have graphical, textual or hybrid syntaxes. Certain domain concepts are better suited to be represented graphically, whereas a textual representation is often more appropriate for modeling the behavior, complex expressions, and fine details of a domain. As such, the best of both worlds of graphical and textual modeling can be delivered by a DSL that has a hybrid (part-graphical and part-textual) syntax. The engineering of hybrid graphical-textual DSLs and their supporting workbenches is a non-trivial endeavor, as a substantial amount of hand-written code is required. Existing workbenches for hybrid graphical-textual DSLs pose several limitations, e.g., they do not enforce the consistency between the graphical and textual parts of the model and do not provide uniform error reporting. This work will propose a methodology and provide tooling for systematic engineering that aims to minimize the accidental complexity involved in designing and developing hybrid graphical-textual DSLs and their supporting workbenches.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | This is an author-produced version of the published paper. Uploaded in accordance with the University’s Research Publications and Open Access policy. |
Keywords: | Domain-Specific Languages,Graphical-Textual Modeling,Language Engineering,Model Editors |
Dates: |
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Institution: | The University of York |
Academic Units: | The University of York > Faculty of Sciences (York) > Computer Science (York) |
Funding Information: | Funder Grant number INNOVATE UK 113213/SUP-00007484 |
Depositing User: | Pure (York) |
Date Deposited: | 05 Feb 2024 09:20 |
Last Modified: | 07 Mar 2025 00:02 |
Published Version: | https://doi.org/10.1109/MODELS-C59198.2023.00041 |
Status: | Published |
Publisher: | IEEE |
Identification Number: | 10.1109/MODELS-C59198.2023.00041 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:208677 |
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