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Scalable race detection for Android applications

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OOPSLA 2015: Proceedings of the 2015 ACM SIGPLAN International Conference on Object-Oriented Programming, Systems, Languages, and Applications

Pages 332 - 348

https://doi.org/10.1145/2814270.2814303

Published: 23 October 2015 Publication History

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Abstract

We present a complete end-to-end dynamic analysis system for finding data races in mobile Android applications. The capabilities of our system significantly exceed the state of the art: our system can analyze real-world application interactions in minutes rather than hours, finds errors inherently beyond the reach of existing approaches, while still (critically) reporting very few false positives. Our system is based on three key concepts: (i) a thorough happens-before model of Android-specific concurrency, (ii) a scalable analysis algorithm for efficiently building and querying the happens-before graph, and (iii) an effective set of domain-specific filters that reduce the number of reported data races by several orders of magnitude. We evaluated the usability and performance of our system on 354 real-world Android applications (e.g., Facebook). Our system analyzes a minute of end-user interaction with the application in about 24 seconds, while current approaches take hours to complete. Inspecting the results for 8 large open-source applications revealed 15 harmful bugs of diverse kinds. Some of the bugs we reported were confirmed and fixed by developers.

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Cited By

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Guo XQi XLi YWu C(2024)PredRacer: Predictively Detecting Data Races in Android Applications2024 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER)10.1109/SANER60148.2024.00031(239-249)Online publication date: 12-Mar-2024
https://doi.org/10.1109/SANER60148.2024.00031
Abdulla PAtig MBønneland FDas SJonsson BLång MSagonas K(2023)Tailoring Stateless Model Checking for Event-Driven Multi-threaded ProgramsAutomated Technology for Verification and Analysis10.1007/978-3-031-45332-8_9(176-198)Online publication date: 19-Oct-2023
https://doi.org/10.1007/978-3-031-45332-8_9
Li CChen RWang BYu TGao DYang MRyu SSmaragdakis Y(2022)Precise and efficient atomicity violation detection for interrupt-driven programs via staged path pruningProceedings of the 31st ACM SIGSOFT International Symposium on Software Testing and Analysis10.1145/3533767.3534412(506-518)Online publication date: 18-Jul-2022
https://dl.acm.org/doi/10.1145/3533767.3534412
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Scalable race detection for Android applications

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Race detection for Android applications
PLDI '14: Proceedings of the 35th ACM SIGPLAN Conference on Programming Language Design and Implementation

Programming environments for smartphones expose a concurrency model that combines multi-threading and asynchronous event-based dispatch. While this enables the development of efficient and feature-rich applications, unforeseen thread interleavings ...
Scalable race detection for Android applications
OOPSLA '15

We present a complete end-to-end dynamic analysis system for finding data races in mobile Android applications. The capabilities of our system significantly exceed the state of the art: our system can analyze real-world application interactions in ...
Race detection for Android applications
PLDI '14

Programming environments for smartphones expose a concurrency model that combines multi-threading and asynchronous event-based dispatch. While this enables the development of efficient and feature-rich applications, unforeseen thread interleavings ...

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Information

Published In

OOPSLA 2015: Proceedings of the 2015 ACM SIGPLAN International Conference on Object-Oriented Programming, Systems, Languages, and Applications

October 2015

953 pages

ISBN:9781450336895

DOI:10.1145/2814270

General Chair:
Jonathan Aldrich
Carnegie Mellon University, USA
,
Program Chair:
Patrick Eugster
Purdue University, USA

ACM SIGPLAN Notices Volume 50, Issue 10
OOPSLA '15
October 2015
953 pages
ISSN:0362-1340
EISSN:1558-1160
DOI:10.1145/2858965
Editor:
Andy Gill
University of Kansas, Lawrence, KS
Issue’s Table of Contents

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 23 October 2015

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SPLASH '15

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SIGPLAN

SPLASH '15: Conference on Systems, Programming, Languages, and Applications: Software for Humanity

October 25 - 30, 2015

PA, Pittsburgh, USA

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Overall Acceptance Rate 268 of 1,244 submissions, 22%

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Cited By

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Guo XQi XLi YWu C(2024)PredRacer: Predictively Detecting Data Races in Android Applications2024 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER)10.1109/SANER60148.2024.00031(239-249)Online publication date: 12-Mar-2024
https://doi.org/10.1109/SANER60148.2024.00031
Abdulla PAtig MBønneland FDas SJonsson BLång MSagonas K(2023)Tailoring Stateless Model Checking for Event-Driven Multi-threaded ProgramsAutomated Technology for Verification and Analysis10.1007/978-3-031-45332-8_9(176-198)Online publication date: 19-Oct-2023
https://doi.org/10.1007/978-3-031-45332-8_9
Li CChen RWang BYu TGao DYang MRyu SSmaragdakis Y(2022)Precise and efficient atomicity violation detection for interrupt-driven programs via staged path pruningProceedings of the 31st ACM SIGSOFT International Symposium on Software Testing and Analysis10.1145/3533767.3534412(506-518)Online publication date: 18-Jul-2022
https://dl.acm.org/doi/10.1145/3533767.3534412
Su TFan LChen SLiu YXu LPu GSu Z(2022)Why My App Crashes? Understanding and Benchmarking Framework-Specific Exceptions of Android AppsIEEE Transactions on Software Engineering10.1109/TSE.2020.301343848:4(1115-1137)Online publication date: 1-Apr-2022
https://doi.org/10.1109/TSE.2020.3013438
Qiu ZShao SZhao QJin GSpinellis DGousios GChechik MDi Penta M(2021)Understanding and detecting server-side request races in web applicationsProceedings of the 29th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering10.1145/3468264.3468594(842-854)Online publication date: 20-Aug-2021
https://dl.acm.org/doi/10.1145/3468264.3468594
Dong ZTiwari AYu XRoychoudhury ASpinellis DGousios GChechik MDi Penta M(2021)Flaky test detection in Android via event order explorationProceedings of the 29th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering10.1145/3468264.3468584(367-378)Online publication date: 20-Aug-2021
https://dl.acm.org/doi/10.1145/3468264.3468584
Chang XDou WWei JHuang TXie JDeng YYang JYang J(2021)Race Detection for Event-Driven Node.js Applications2021 36th IEEE/ACM International Conference on Automated Software Engineering (ASE)10.1109/ASE51524.2021.9678814(480-491)Online publication date: Nov-2021
https://doi.org/10.1109/ASE51524.2021.9678814
Liu AAlqazzaz AMing HDharmalingam B(2021)Iotverif: Automatic Verification of SSL/TLS Certificate for IoT ApplicationsIEEE Access10.1109/ACCESS.2019.29619189(27038-27050)Online publication date: 2021
https://doi.org/10.1109/ACCESS.2019.2961918
Li XZhang LShen X(2020)DIACACM Transactions on Embedded Computing Systems10.1145/339189519:6(1-25)Online publication date: 3-Oct-2020
https://dl.acm.org/doi/10.1145/3391895
Salehnamadi NAlshayban AAhmed IMalek Sde Lara EMohomed INieh JBelding E(2020)A benchmark for event-race analysis in android appsProceedings of the 18th International Conference on Mobile Systems, Applications, and Services10.1145/3386901.3396602(466-467)Online publication date: 15-Jun-2020
https://dl.acm.org/doi/10.1145/3386901.3396602
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