The TAU Programming Languages and Systems Seminar - Inferring Inductive Invariants from Phase Structures

Abstract:

Infinite-state systems such as distributed protocols are challenging to verify using interactive theorem provers or automatic verification tools. Of these techniques, deductive verification is highly expressive but requires the user to annotate the system with inductive invariants. To relieve the user from this labor-intensive and challenging task, invariant inference aims to find inductive invariants automatically. Unfortunately, when applied to infinite-state systems such as distributed protocols, existing inference techniques often diverge, which greatly limits their applicability.

This paper proposes user-guided invariant inference based on phase invariants, which capture the different logical phases of the protocol. The user conveys their intuition by specifying a phase structure, an automaton with edges labeled by program transitions; the tool automatically infers assertions that hold in the automaton's states, resulting in a full safety proof. The additional structure of phases provides guidance to the inference procedure about how to find an invariant. 

Our results show that user guidance by phase structures facilitates successful inference beyond the state of the art. We find that phase structures are pleasantly well matched to the intuitive reasoning routinely used by domain experts to understand why distributed protocols are correct, so that providing a phase structure reuses this existing intuition. 

Joint work with James R. Wilcox, Sharon Shoham, and Mooly Sagiv.