Enabling the Development of Cognitive Effective Visual DSLs

The development of graphical editors for visual DSLs is far from being a trivial task. There are consequently several tools that provide technical support for this task. However, this paper shows that the analysis of the main characteristics of such tools leaves some space for improvement as regard the cognitive effectiveness of the visual notations produced with them. To deal with this issue, this work introduces CEViNEdit, a GMF-based framework for the development of visual DSLs which takes into account Moody’s principles for the development and evaluation of graphical notations. To that end, CEViNEdit eases the selection of values for the visual variables of which the notation is composed, computes a set of metrics to assess the appropriateness of these values and then automates the generation of the graphical editor.

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