Transformation by example
Houari A. Sahraoui, Mounir Boukadoum, Marouane Kessentini · 2010
Model transformations take as input a source model and generate as output a target model. The source and target models conform to given meta-models. We distinguish between two transformation categories. Exogenous transformations are transformations between models expressed using different languages, and the whole source model is transformed. Endogenous transformations are transformations between models expressed in the same language. For endogenous transformations, two steps are needed: identifying the source model elements to transform and then applying the transformation on them. In this thesis, we propose three principal contributions. The first contribution aims to automate model transformations. The process is seen as an optimization problem where different transformation possibilities are evaluated and, for each possibility, a quality is associated depending on its conformity with a reference set of examples. This first contribution can be applied to exogenous as well as endogenous transformation (after determining the source model elements to transform). The second contribution is related precisely to the detection of elements concerned with endogenous transformations. In this context, we present a new technique for design defect detection. The detection is based on the notion that the more a code deviates from good practice, the more likely it is bad. Taking inspiration from artificial immune systems, we generate a set of detectors that characterize the ways in which a code can diverge from good practices. We then use these detectors to determine how far the code in the assessed systems deviates from normality. The third contribution concerns transformation mechanism testing. The proposed oracle function compares target test cases with a base of examples containing good quality transformation traces, and assigns a risk level based on the dissimilarity between the two. The traces help the tester understand the origin of an error. The three contributions are evaluated with real software projects and the obtained results confirm their efficiencies. Keywords: Model-driven engineering, by example, design defects, search-based software engineering, artificial immune-system