IC3 - Flipping the E in ICE

Yakir Vizel, Arie Gurfinkel, Sharon Shoham, Sharad Malik

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Scopus citations


Induction is a key element of state-of-the-art verification techniques. Automatically synthesizing and verifying inductive invariants is at the heart of Model Checking of safety properties. In this paper, we study the relationship between two popular approaches to synthesizing inductive invariants: SAT-based Model Checking (SAT-MC) and Machine Learning-based Invariant Synthesis (MLIS). Our goal is to identify and formulate the theoretical similarities and differences between the two frameworks. We focus on two flagship algorithms: IC3 (an instance of SAT-MC) and ICE (an instance of MLIS). We show that the two frameworks are very similar yet distinct. For a meaningful comparison, we introduce RICE, an extension of ICE with relative induction and show how IC3 can be implemented as an instance of RICE. We believe this work contributes to the understanding of inductive invariant synthesis and will serve as a foundation for further improvements to both SAT-MC and MLIS algorithms.

Original languageEnglish (US)
Title of host publicationVerification, Model Checking, and Abstract Interpretation - 18th International Conference, VMCAI 2017, Proceedings
EditorsAhmed Bouajjani, David Monniaux
PublisherSpringer Verlag
Number of pages18
ISBN (Print)9783319522333
StatePublished - 2017
Event18th International Conference on Verification, Model Checking, and Abstract Interpretation, VMCAI 2017 - Paris, France
Duration: Jan 15 2017Jan 17 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10145 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other18th International Conference on Verification, Model Checking, and Abstract Interpretation, VMCAI 2017

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science


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