Quality assurance for machine-learning programs and notebooks
We are pleased to invite you to an open workshop presenting our ongoing research project, conducted in collaboration with WASP, on quality assurance for machine-learning (ML) programs and notebooks. Machine-learning software differs fundamentally from traditional software in development practices, organizational roles, and strong dependency on training data. However, software quality assurance (QA) aiming to ensure robustness, maintainability, and functional correctness is much less established than those for engineering traditional software.