We presented the poster "Predicting Bad Commits" at DVCon, Feb 26 2019, San Jose, CA , where we explored the feasibility of using machine learning to predict bugs. Bug prediction occurs before tests are launched. At this time there is not even a test failure to analyze.

The idea is that the better you can predict bugs the better you can control the verification flow. This means that you can control whether to run a large/small test suite depending on how risky the recent changes are. Also debugging of bugs takes less time as you know the most likely culprits before you start.

We also participated in a round table discussion on AI and EDA, which will end up as an article series by Brian Baily in semiengineering.com

Larry Melling (Cadence), Harry Foster (Mentor), Daniel Hansson (Verifyter), Manish Pandey (Carnegie Mellon), Doug Letcher (Metrics), Raik Brinkmann (OneSpin) 

At our booth we talked about bug prediction and automatic debug at our booth, which had quite a few visitors. According to our scientific studies machine learning attracts more engineers than candy these days :-)