From Input to Failure: Explaining Program Behavior via Cause-Effect Chains

Debugging a fault in a program is an error-prone and resource-intensive process that requires considerable work. My doctoral research aims at supporting developers during this process by integrating test generation as a feedback loop into a novel fault diagnosis to narrow down the causality by validating or disproving suggested hypotheses. I will combine input, output, and state to detect relevant relations for an immersive fault diagnosis. Further, I want to introduce an approach for a targeted test that leverages statistical fault localization to extract oracles based on execution features to identify failing tests.