Program Analysis with Local Policy Iteration
Abstract
We present a new algorithm for deriving numerical invariants that combines the precision of max-policy iteration with the flexibility and scalability of conventional Kleene iterations. It is defined in the Configurable Program Analysis (CPA) framework, thus allowing inter-analysis communication. It uses adjustable-block encoding in order to traverse loop-free program sections, possibly containing branching, without introducing extra abstraction. Our technique operates over any template linear constraint domain, including the interval and octagon domains; templates can also be derived from the program source. The implementation is evaluated on a set of benchmarks from the Software Verification Competition (SV-Comp). It competes favorably with state-of-the-art analyzers.
Cite
@article{arxiv.1509.03424,
title = {Program Analysis with Local Policy Iteration},
author = {George Karpenkov and David Monniaux and Philipp Wendler},
journal= {arXiv preprint arXiv:1509.03424},
year = {2016}
}