“…Keeper [30] is a tool for testing software using cognitive ML APIs that utilizes pseudo-inverse functions, symbolic execution, and automatic generation of test inputs to fulfill branch coverage and identify root causes of bugs. DeepDiagnosis [32] is an approach for debugging DNN programs by identifying and localizing faults, such as an exploding tensor or loss not decreasing during training, as well as suggesting fixes for the root causes of the faults. Another work [28] proposes enabling ML libraries to search for hyperparameter configurations that encourage learning a fair model, given the dataset.…”