Grounding Deep Learning Framework Testing in Data Flow
FlowMuT is a mutation-based testing technique for deep learning frameworks that uses a Tensor Flow Graph (TFG) to track data flow and operator requirements during execution. It systematically generates and selects mutations based on this flow information, successfully detecting 79 bugs compared to 28 in the strongest baseline. This method significantly improves bug detection, diversity, and coverage.