In model-driven software engineering (MDSE), the declarative graph transformation language Henshin transforms instance models represented as graphs by applying a series of basic steps that match and substitute structural patterns on parts of models. These simple transformation rules are then combined in control flow constructs similar to those of imperative programming languages to build more complex transformations.

However, defects in the structure of control flow or in transformation rules might schedule the application of operations incorrectly, thereby causing basic steps to not be applicable at all or produce wrong output. Understanding and fixing these bugs is complicated by the fact that pattern matching in rules is nondeterministic. Moreover, some control flow structures employ a nondeterministic choice of alternatives. This makes it challenging for developers to keep track of all the possible execution paths and interactions between them.

For conventional programming languages, techniques have been developed to execute a program symbolically. By abstracting over the concrete values of variables in any actual run, generalized knowledge about the possible behavior of the program is gained. This can be helpful in understanding problems and fixing bugs. In this paper, we discuss techniques from the domain of symbolic execution and their adaption to graph transformations. We outline an approach to support analysis and debugging of complex transformations, aimed at a subset of the declarative graph transformation language Henshin.