Interval Analysis in Industrial-Scale BMC Software Verifiers: A Case Study

TL;DR

This paper evaluates the effectiveness of interval analysis in improving the performance of bounded model checking (BMC) for software verification, demonstrating its importance in solving complex benchmarks despite computational costs.

Contribution

The study provides a comprehensive assessment of interval analysis in industrial-scale BMC, quantifying its benefits and identifying benchmarks where it is essential.

Findings

Interval analysis solves 203 unique benchmarks.

It significantly improves BMC performance on complex cases.

The computational cost is justified by the performance gains.

Abstract

Bounded Model Checking (BMC) is a widely used software verification technique. Despite its successes, the technique has several limiting factors, from state-space explosion to lack of completeness. Over the years, interval analysis has repeatedly been proposed as a partial solution to these limitations. In this work, we evaluate whether the computational cost of interval analysis yields significant enough improvements in BMC's performance to justify its use. In more detail, we quantify the benefits of interval analysis on two benchmarks: the Intel Core Power Management firmware and 9537 programs in the ReachSafety category of the International Competition on Software Verification. Our results show that interval analysis is essential in solving 203 unique benchmarks.