Refining Trace Abstraction using Abstract Interpretation

TL;DR

This paper introduces a novel approach combining abstract interpretation with SMT solving to improve trace abstraction refinement in software model checking, especially for programs with loops, enhancing convergence and efficiency.

Contribution

It presents a new refinement procedure that leverages abstract interpretation to derive loop invariants, reducing reliance on SMT solvers and improving divergence issues in CEGAR loops.

Findings

Effective in deriving loop invariants from traces.

Reduces SMT solver calls by using abstract interpretation.

Shows practical potential through experimental evaluation.

Abstract

The CEGAR loop in software model checking notoriously diverges when the abstraction refinement procedure does not derive a loop invariant. An abstraction refinement procedure based on an SMT solver is applied to a trace, i.e., a restricted form of a program (without loops). In this paper, we present a new abstraction refinement procedure that aims at circumventing this restriction whenever possible. We apply abstract interpretation to a program that we derive from the given trace. If the program contains a loop, we are guaranteed to obtain a loop invariant. We call an SMT solver only in the case where the abstract interpretation returns an indefinite answer. That is, the idea is to use abstract interpretation and an SMT solver in tandem. An experimental evaluation in the setting of trace abstraction indicates the practical potential of this idea.