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Published in: Software and Systems Modeling 3/2021

17-10-2020 | Regular Paper

CEViNEdit: improving the process of creating cognitively effective graphical editors with GMF

Authors: David Granada, Juan M. Vara, Mercedes Merayo, Esperanza Marcos

Published in: Software and Systems Modeling | Issue 3/2021

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Abstract

The rise of domain-specific (Visual) languages and the inherent complexity of developing graphical editors for these languages have led to the emergence of proposals that provide support for this task. Most of these proposals are principally based on EMF and GMF, which effectively help to simplify and increase the level of automation of the development process of the editors, but it is important to recall that these proposals have some important disadvantages, mainly related to the learning curve of these technologies, poor documentation or the complexity of providing all the customisation possibilities to the user. In addition, in the process of developing a domain-specific language, issues related to graphical conventions have historically been undervalued, while most of the effort has been focused on semantic aspects. In fact, definitions of the concrete (visual) syntax of modelling languages in Software Engineering are usually based on common sense, intuition, the reuse of existing notations or emulation of common practices. In order to alleviate the inherent complexity of the EMF/GMF approach for the development of graphical editors and to support the evaluation of the quality of visual notations of modelling languages, this article presents CEViNEdit, an intuitive tool that simultaneously supports the semi-automatic generation of graphical editors and the assessment of the cognitive effectiveness of the visual notation implemented by the editor.

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Metadata
Title
CEViNEdit: improving the process of creating cognitively effective graphical editors with GMF
Authors
David Granada
Juan M. Vara
Mercedes Merayo
Esperanza Marcos
Publication date
17-10-2020
Publisher
Springer Berlin Heidelberg
Published in
Software and Systems Modeling / Issue 3/2021
Print ISSN: 1619-1366
Electronic ISSN: 1619-1374
DOI
https://doi.org/10.1007/s10270-020-00833-2

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