Infoscience

Report

Path Invariants

The success of software verification depends on the ability to find a suitable abstraction of a program automatically. We propose a new method for automated abstraction refinement, which overcomes the inherent limitations of predicate discovery schemes. In such schemes, the cause of a false positive is identified as an infeasible error path, and the abstraction is refined in order to remove that path. By contrast, we view the cause of a false positive ---the spurious counterexample''--- as a full-fledged program, whose control-flow graph may contain loops of the original program and represent unbounded computations. The advantages of using such path programs as counterexamples for abstraction refinement are twofold. First, we can bring the whole machinery of program analysis to bear on path programs: specifically, we use abstract interpretation in the form of constrained-based invariant generation to automatically infer invariants of path programs ---so-called path invariants. Second, we use path invariants for abstraction refinement in order to remove not one infeasibility at a time, but to remove at once all infeasible error computations that are represented by a path program. Unlike predicate discovery schemes, our method handles loops without unrolling them; it infers abstractions that involve universal quantification and naturally incorporates disjunctive invariants.