Type Inference Using Concrete Syntax Properties in Flexible Model-Driven Engineering

In traditional Model-Driven Engineering (MDE) models are instantiated from metamodels. In contrast, in Flexible MDE, language engineers initially create example models of the envisioned metamodel. Due to the lack of a metamodel at the beginning, the example models may include errors like missing types, typos or the use of different types to express the same domain concepts. In previous work [1] an approach that uses semantic properties of the example models to infer the types of the elements that are left untyped was proposed. In this paper, we build on that approach by investigating how concrete syntax properties (like the shape or the color of the elements) of the example models can help in the direction of type inference. We evaluate the approach on an example model. The initial results suggest that on average 64% of the nodes are correctly identified.

• Type: Journal
• Year: 2015
• Where: MODELS
• Authors: Athanasios Zolotas, Nicholas Drivalos Matragkas, Sam Devlin, Dimitrios S. Kolovos, Richard F. Paige
• Keywords: MODELS 2015, Natural Language Processing