Using program induction for verification

Summary: I discussed before (e.g. here) how connecting rule-based verification to the rule-less, amorphous Machine Learning world is really hard, and yet necessary. The current post talks about a somewhat-exotic technique called Program Induction (PI), and how it might (eventually) help bridge that gap. What’s program induction Background: I always liked the idea of synthesizing … More Using program induction for verification

Where Machine Learning meets rule-based verification

Summary: This post addresses some high-level questions like: Longer term, how much of the verification of Intelligent Autonomous Systems can be done with just Machine Learning (ML)? Should most requirements remain rule-based, and if so – how does that connect to the ML part? And how will the uneasy interface between ML and rules influence … More Where Machine Learning meets rule-based verification

About faults and bugs

Summary: This post tries to fit Fault Tree Analysis and CDV-based “normal” bug-finding into the same conceptual framework. FTA and CDV have a challenging, uneasy relationship with each other. In a nutshell (details below): FTA (and similar techniques) is a good, established way to reason about failures and reliability, but (1) it depends on humans … More About faults and bugs