Program Analysis with Local Policy Iteration

We present local policy iteration (LPI), 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. LPI 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 International Competition on Software Verification (SV-COMP). It competes favorably with state-of-the-art analyzers.