Prof. Dr. Matthew Dwyer (University of Virginia)
Keynote: Distribution-aware Test Adequacy for Neural Networks
Prior work that ignores the data distribution can lead to wasted testing effort and inaccurate characterizations of the thoroughness of testing. This talk describes a new approach, called “input distribution coverage” (IDC), that formulates test adequacy measures over the latent distribution of generative models to avoid these problems.
