Towards Methods for Model-Based Software Development

Software engineering is a young discipline. Despite efforts in recent years, some elements still require further development, research, and systematization. One of these elements are methods. They consist of a set of well-defined activities used in a software development to guide how the work should be performed to achieve the expected results. However, there is a lack of systematic knowledge that effectively guide how work should be done in a variety of areas. Despite the knowledge available in Software Engineering Body of Knowledge (SWEBOK), only the classical methods are comprised there, while emerging topics such as Agent-Oriented Software Engineering (AOSE), Aspect-Oriented Software Development (AOSD), and Model-Based Software Development (MBSE) are only briefly mentioned. We claim that it is also necessary to investigate methods for those emerging software engineering subtracks. In this direction, this paper presents a a speculative and preliminary emerging results on the establishment of methods for MBSE. We report some insights on the conception of methods for MBSE

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.