DeCaF combines counterfactual generators and causal models to identify minimal input signal changes that fix CPS failures and derives interpretable assertions that generalize the recovery conditions.
Towards unifying feature attribution and counterfactual explanations: Different means to the same end,
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Towards Counterfactual Explanation and Assertion Inference for CPS Debugging
DeCaF combines counterfactual generators and causal models to identify minimal input signal changes that fix CPS failures and derives interpretable assertions that generalize the recovery conditions.