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.