The Incremental Advantage: Evaluating the Performance of a TGG-based Visualisation Framework
Triple Graph Grammars (TGGs) are best known as a bidirectional model transformation language, which might give the misleading impression that they are wholly unsuitable for unidirectional application scenarios. We believe that it is more useful to regard TGGs as just graph grammars with “batteries included”, meaning that TGG-based tools provide simple, default execution strategies, together with algorithms for incremental change propagation. Especially in cases where the provided execution strategies suffice, a TGG-based infrastructure may be advantageous, even for unidirectional transformations.
In this paper, we demonstrate these advantages by presenting a TGG-based, read-only visualisation framework, which is an integral part of the metamodelling and model transformation tool eMoflon. We argue the advantages of using TGGs for this visualisation application scenario, and provide a quantitative analysis of the runtime complexity and scalability of the realised incremental, unidirectional transformation.