System Verification with Machine Learning Techniques

27 Oct 2017 Li Jiaying ISTD Machine Learning

PhD Student
Li Jiaying, Information Systems Technology and Design

Sun Jun, Associate Professor, Information Systems Technology and Design

This research project proposes using machine learning techniques—in particular, classification and active learning—to generate loop invariants.
In a programming system, loop invariants are properties that do not change when a sequence of instructions is continuously repeated. Generating loop invariants is important for system verification, i.e. to verify that a programming system satisfies certain properties.
The proposed machine learning techniques complement existing approaches in finding loop invariants and facilitate system design in the early stage.

Read more here.