Property Directed Self Composition

Ron Shemer*, Arie Gurfinkel, Sharon Shoham, Yakir Vizel

*Corresponding author for this work

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

27 Scopus citations


We address the problem of verifying k-safety properties: properties that refer to k interacting executions of a program. A prominent way to verify k-safety properties is by self composition. In this approach, the problem of checking k-safety over the original program is reduced to checking an “ordinary” safety property over a program that executes k copies of the original program in some order. The way in which the copies are composed determines how complicated it is to verify the composed program. We view this composition as provided by a semantic self composition function that maps each state of the composed program to the copies that make a move. Since the “quality” of a self composition function is measured by the ability to verify the safety of the composed program, we formulate the problem of inferring a self composition function together with the inductive invariant needed to verify safety of the composed program, where both are restricted to a given language. We develop a property-directed inference algorithm that, given a set of predicates, infers composition-invariant pairs expressed by Boolean combinations of the given predicates, or determines that no such pair exists. We implemented our algorithm and demonstrate that it is able to find self compositions that are beyond reach of existing tools.

Original languageEnglish
Title of host publicationComputer Aided Verification - 31st International Conference, CAV 2019, Proceedings
EditorsIsil Dillig, Serdar Tasiran
PublisherSpringer Verlag
Number of pages19
ISBN (Print)9783030255398
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)
Volume11561 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


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


FundersFunder number
Horizon 2020 Framework Programme759102
Blavatnik Family Foundation
European Research Council
United States-Israel Binational Science Foundation2016260
Israel Science Foundation1810/18
Tel Aviv University


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