Dynamic Backward Slicing of Model Transformations

Model transformations are frequently used means for automating software development in various domains to improve quality and reduce production costs. Debugging of model transformations often necessitates identifying parts of the transformation program and the transformed models which have causal dependence on a selected statement. In traditional programming environments, program slicing techniques are widely used to calculate control and data dependencies between the statements of the program. Here we introduce program slicing for model transformations where the main challenge is to simultaneously assess data and control dependencies over the transformation program and the underlying models of the transformation. In this paper, we present a dynamic backward slicing approach for both model transformation programs and their transformed models based on automatically generated execution trace models of transformations. We evaluate our approach using different transformation case studies.