Summary: This post will take an initial look at the US Autonomous Vehicles policy announcement, and claim it is a big deal. It will then examine the verification implications, and claim they are mainly positive. Yesterday, the US Department of Transportation (DOT) and the National Highway Traffic Safety Administration (NHTSA) came out with an announcement … More Verification implications of the new US AV policy
Summary: Can one use ML to verify ML-based systems? This post claims the answer is mostly “no”: You mainly have to use other system verification methodologies. However, some ML-based techniques may still be quite useful. How does one verify ML-based systems? A previous post in this series claimed that the “right” way is CDV: Essentially, … More Using Machine Learning to verify Machine Learning?
Summary: This post describes in general terms the problem of “using ML for coverage maximization”, explains why it is important for CDV and for fuzzing, and gives some references. My first post in the “ML and verification” series talked about verifying ML-based systems (lots more to say about that). This post talks about the other … More Machine Learning for Coverage Maximization