Inferring inductive invariants from phase structures

Yotam M.Y. Feldman, James R. Wilcox, Sharon Shoham, Mooly Sagiv

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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 limits their applicability. This paper proposes user-guided invariant inference based on phase invariants, which capture the different logical phases of the protocol. Users 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 from phases guides the inference procedure towards finding 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.

Original languageEnglish
Title of host publicationComputer Aided Verification - 31st International Conference, CAV 2019, Proceedings
EditorsIsil Dillig, Serdar Tasiran
PublisherSpringer Verlag
Pages405-425
Number of pages21
ISBN (Print)9783030255428
DOIs
StatePublished - 2019
Event31st International Conference on Computer Aided Verification, CAV 2019 - New York City, United States
Duration: 15 Jul 201918 Jul 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11562 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference31st International Conference on Computer Aided Verification, CAV 2019
Country/TerritoryUnited States
CityNew York City
Period15/07/1918/07/19

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