Generating Metamodels from Grammars by Chaining Translational and By-Example Techniques.

Abstract

Bridging grammarware and modelware is still challenging, though often required as a prerequisite for several model-driven engineering scenarios. For instance, in model-driven reverse engineering, program code has to be lifted to the model level before model-driven techniques are applicable. Manually building metamodels based on given grammars introduces a significant overhead and may lead to inconsistencies between the resulting metamodels and the grammars, especially when dealing with large languages. In previous work, we have investigated a purely translational approach that is able to semi-automatically generate metamodels from grammars by utilizing user input. In this work, we aim to provide a higher degree of automation by combining the translational approach with by-example techniques to reduce the manual effort. In particular, knowledge is derived from concrete programs to further refine the produced metamodels. We demonstrate a transformation chain that combines translational and by-example techniques to produce Ecore-based metamodels from EBNFbased grammars.