Somin Kim

DANDI: Diffusion as Normative Distribution for Deep Neural Network Input

2025 · arXiv (Cornell University)

Surprise Adequacy (SA) has been widely studied as a test adequacy metric that can effectively guide software engineers towards inputs that are more likely to reveal unexpected behaviour of Deep Neural Networks (DNNs). Intuitively, SA …