Property directed abstract interpretation

Noam Rinetzky, Sharon Shoham*

*Corresponding author for this work

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

2 Scopus citations

Abstract

Recently, Bradley proposed the PDR/IC3 model checking algorithm for verifying safety properties, where forward and backward reachability analyses are intertwined, and guide each other. Many variants of Bradley’s original algorithm have been developed and successfully applied to both hardware and software verification. However, these algorithms have been presented in an operational manner, in disconnect with the rich literature concerning the theoretical foundation of static analysis formulated by abstract interpretation. Inspired by PDR, we develop a nonstandard semantics which computes for every 0 ≤ N an over-approximation of the set of traces of length N leading to a safety violation. The over approximation is precise, in the sense that it only includes traces that do not start at an initial state, unless the program is unsafe, and in this case the semantics aborts at a special error state. In a way, the semantics computes multiple over- approximations of bounded unsafe program behaviors using a sequence of abstractions whose precision grows automatically with N. We show that existing PDR algorithms can be described as a specific implementation of our semantics, performing an abstract interpretation of the program, but instead of aiming for a fixpoint, they stop early when either the backward analysis finds a counterexample or the states com- prising one of the bounded traces provides sufficient evidence that the program is safe. This places PDR within the solid framework of abstract interpretation, and thus provides a unified explanation of the different PDR algorithms as well as a new proof of their soundness.

Original languageEnglish
Title of host publicationVerification, Model Checking, and Abstract Interpretation - 17th International Conference, VMCAI 2016, Proceedings
EditorsK. Rustan, M. Leino, Barbara Jobstmann
PublisherSpringer Verlag
Pages104-123
Number of pages20
ISBN (Print)9783662491218
DOIs
StatePublished - 2016
Event17th International Conference on Verification, Model Checking, and Abstract Interpretation, VMCAI 2016 - St. Petersburg, United States
Duration: 17 Jan 201619 Jan 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9583
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference17th International Conference on Verification, Model Checking, and Abstract Interpretation, VMCAI 2016
Country/TerritoryUnited States
CitySt. Petersburg
Period17/01/1619/01/16

Funding

FundersFunder number
Broadcom Foundation
Seventh Framework Programme308830
European Research Council321174-VSSC
United States-Israel Binational Science Foundation2012259
Tel Aviv University

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