research-article

Data races vs. data race bugs: telling the difference with portend

Authors:

Cristian Zamfir,

George CandeaAuthors Info & Claims

ACM SIGARCH Computer Architecture News, Volume 40, Issue 1

Pages 185 - 198

https://doi.org/10.1145/2189750.2150997

Published: 03 March 2012 Publication History

Abstract

Even though most data races are harmless, the harmful ones are at the heart of some of the worst concurrency bugs. Alas, spotting just the harmful data races in programs is like finding a needle in a haystack: 76%-90% of the true data races reported by state-of-the-art race detectors turn out to be harmless [45]. We present Portend, a tool that not only detects races but also automatically classifies them based on their potential consequences: Could they lead to crashes or hangs? Could their effects be visible outside the program? Are they harmless? Our proposed technique achieves high accuracy by efficiently analyzing multiple paths and multiple thread schedules in combination, and by performing symbolic comparison between program outputs.

We ran Portend on 7 real-world applications: it detected 93 true data races and correctly classified 92 of them, with no human effort. 6 of them are harmful races. Portend's classification accuracy is up to 88% higher than that of existing tools, and it produces easy-to-understand evidence of the consequences of harmful races, thus both proving their harmfulness and making debugging easier. We envision Portend being used for testing and debugging, as well as for automatically triaging bug reports.

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Cited By

Genç KRoemer JXu YBond M(2019)Dependence-aware, unbounded sound predictive race detectionProceedings of the ACM on Programming Languages10.1145/33606053:OOPSLA(1-30)Online publication date: 10-Oct-2019
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Index Terms

Data races vs. data race bugs: telling the difference with portend
1. Software and its engineering
  1. Software creation and management
    1. Software verification and validation

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Published In

cover image ACM SIGARCH Computer Architecture News

ACM SIGARCH Computer Architecture News Volume 40, Issue 1

ASPLOS '12

March 2012

453 pages

ISSN:0163-5964

DOI:10.1145/2189750

Issue’s Table of Contents

ASPLOS XVII: Proceedings of the seventeenth international conference on Architectural Support for Programming Languages and Operating Systems
March 2012
476 pages
ISBN:9781450307598
DOI:10.1145/2150976
General Chair:
Tim Harris
Microsoft Research
,
Program Chair:
Michael L. Scott
University of Rochester

Copyright © 2012 ACM.

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Published: 03 March 2012

Published in SIGARCH Volume 40, Issue 1

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Cited By

Genç KRoemer JXu YBond M(2019)Dependence-aware, unbounded sound predictive race detectionProceedings of the ACM on Programming Languages10.1145/33606053:OOPSLA(1-30)Online publication date: 10-Oct-2019
https://dl.acm.org/doi/10.1145/3360605
Li GLiu HChen XGunawi HLu SMcKinley KFisher K(2019)DFix: automatically fixing timing bugs in distributed systemsProceedings of the 40th ACM SIGPLAN Conference on Programming Language Design and Implementation10.1145/3314221.3314620(994-1009)Online publication date: 8-Jun-2019
https://dl.acm.org/doi/10.1145/3314221.3314620
Wang PLu KLi GZhou X(2019)DFTrackerFrontiers of Computer Science: Selected Publications from Chinese Universities10.1007/s11704-016-6383-813:2(247-263)Online publication date: 1-Apr-2019
https://dl.acm.org/doi/10.1007/s11704-016-6383-8
Gao JYang XJiang YLiu HYing WSun WGu MTip FBodden E(2018)Managing concurrent testing of data race with ComRaDeProceedings of the 27th ACM SIGSOFT International Symposium on Software Testing and Analysis10.1145/3213846.3229502(364-367)Online publication date: 12-Jul-2018
https://dl.acm.org/doi/10.1145/3213846.3229502
Yu TSrisa-an WRothermel G(2017)An automated framework to support testing for process‐level race conditionsSoftware Testing, Verification and Reliability10.1002/stvr.163427:4-5Online publication date: 10-May-2017
https://doi.org/10.1002/stvr.1634
Cao MRoemer JSengupta ABond M(2016)Prescient memory: exposing weak memory model behavior by looking into the futureACM SIGPLAN Notices10.1145/3241624.292670051:11(99-110)Online publication date: 14-Jun-2016
https://dl.acm.org/doi/10.1145/3241624.2926700
Cao MRoemer JSengupta ABond MFlood CZhang Z(2016)Prescient memory: exposing weak memory model behavior by looking into the futureProceedings of the 2016 ACM SIGPLAN International Symposium on Memory Management10.1145/2926697.2926700(99-110)Online publication date: 14-Jun-2016
https://dl.acm.org/doi/10.1145/2926697.2926700
Zhang WYu SWang HDai ZChen H(2016)Hardware Support for Concurrent Detection of Multiple Concurrency Bugs on Fused CPU-GPU ArchitecturesIEEE Transactions on Computers10.1109/TC.2015.251286065:10(3083-3095)Online publication date: 1-Oct-2016
https://dl.acm.org/doi/10.1109/TC.2015.2512860
Murillo LWawroschek SCastrillon JLeupers RAscheid GFettweis GNebel W(2014)Automatic detection of concurrency bugs through event ordering constraintsProceedings of the conference on Design, Automation & Test in Europe10.5555/2616606.2617019(1-6)Online publication date: 24-Mar-2014
https://dl.acm.org/doi/10.5555/2616606.2617019
Ruwase OKozuch MGibbons PMowry T(2014)GuardrailACM SIGARCH Computer Architecture News10.1145/2654822.254197042:1(655-670)Online publication date: 24-Feb-2014
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