A New Approach for Minimal Environment Construction for Modular Property Verification

Abstract

In this work, we propose a framework for construction of an approximate environment for compositional verification using invariants learned from dynamic traces of the system and the counterexamples generated by a model checker on verifying a property on the component in isolation. We adopt a counterexample ranking methodology for eliminating possibly fictitious counterexamples by choosing a minimal subset of the invariants. We explore the aspect of choosing a threshold for counterexamples as well as assume properties which can contribute towards further refining the subset chosen and produce a stronger abstraction. Experimental results on benchmark designs shows the efficacy of our proposal.