research-article

Taming Android fragmentation: characterizing and detecting compatibility issues for Android apps

Authors:

Shing-Chi CheungAuthors Info & Claims

ASE '16: Proceedings of the 31st IEEE/ACM International Conference on Automated Software Engineering

Pages 226 - 237

https://doi.org/10.1145/2970276.2970312

Published: 25 August 2016 Publication History

Abstract

Android ecosystem is heavily fragmented. The numerous combinations of different device models and operating system versions make it impossible for Android app developers to exhaustively test their apps. As a result, various compatibility issues arise, causing poor user experience. However, little is known on the characteristics of such fragmentation-induced compatibility issues and no mature tools exist to help developers quickly diagnose and fix these issues. To bridge the gap, we conducted an empirical study on 191 real-world compatibility issues collected from popular open-source Android apps. Our study characterized the symptoms and root causes of compatibility issues, and disclosed that the patches of these issues exhibit common patterns. With these findings, we propose a technique named FicFinder to automatically detect compatibility issues in Android apps. FicFinder performs static code analysis based on a model that captures Android APIs as well as their associated context by which compatibility issues are triggered. FicFinder reports actionable debugging information to developers when it detects potential issues. We evaluated FicFinder with 27 large-scale open-source Android apps. The results show that FicFinder can precisely detect compatibility issues in these apps and uncover previously-unknown issues.

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Cited By

Mobilio MRiganelli OMicucci DMariani L(2024)FILO: Automated FIx-LOcus Identification for Android Framework Compatibility IssuesInformation10.3390/info1508042315:8(423)Online publication date: 23-Jul-2024
https://doi.org/10.3390/info15080423
Dong ZZhao YLiu TWang CXu GXu GZhang LWang HFilkov VRay BZhou M(2024)Same App, Different Behaviors: Uncovering Device-specific Behaviors in Android AppsProceedings of the 39th IEEE/ACM International Conference on Automated Software Engineering10.1145/3691620.3695272(2099-2109)Online publication date: 27-Oct-2024
https://dl.acm.org/doi/10.1145/3691620.3695272
Yu SFang CLi XLing YChen ZSu Z(2024)Effective, Platform-Independent GUI Testing via Image Embedding and Reinforcement LearningACM Transactions on Software Engineering and Methodology10.1145/367472833:7(1-27)Online publication date: 21-Jun-2024
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Index Terms

Taming Android fragmentation: characterizing and detecting compatibility issues for Android apps

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cover image ACM Conferences

ASE '16: Proceedings of the 31st IEEE/ACM International Conference on Automated Software Engineering

August 2016

899 pages

ISBN:9781450338455

DOI:10.1145/2970276

General Chair:
David Lo
Singapore Management University, Singapore
,
Program Chairs:
Sven Apel
University of Passau, Germany
,
Sarfraz Khurshid
University of Texas at Austin, USA

Copyright © 2016 ACM.

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Published: 25 August 2016

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ASE'16: ACM/IEEE International Conference on Automated Software Engineering

September 3 - 7, 2016

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Cited By

Mobilio MRiganelli OMicucci DMariani L(2024)FILO: Automated FIx-LOcus Identification for Android Framework Compatibility IssuesInformation10.3390/info1508042315:8(423)Online publication date: 23-Jul-2024
https://doi.org/10.3390/info15080423
Dong ZZhao YLiu TWang CXu GXu GZhang LWang HFilkov VRay BZhou M(2024)Same App, Different Behaviors: Uncovering Device-specific Behaviors in Android AppsProceedings of the 39th IEEE/ACM International Conference on Automated Software Engineering10.1145/3691620.3695272(2099-2109)Online publication date: 27-Oct-2024
https://dl.acm.org/doi/10.1145/3691620.3695272
Yu SFang CLi XLing YChen ZSu Z(2024)Effective, Platform-Independent GUI Testing via Image Embedding and Reinforcement LearningACM Transactions on Software Engineering and Methodology10.1145/367472833:7(1-27)Online publication date: 21-Jun-2024
https://dl.acm.org/doi/10.1145/3674728
Igbomezie MNguyen PDi Ruscio D(2024)When simplicity meets effectiveness: Detecting code comments coherence with word embeddings and LSTMProceedings of the 28th International Conference on Evaluation and Assessment in Software Engineering10.1145/3661167.3661187(411-416)Online publication date: 18-Jun-2024
https://dl.acm.org/doi/10.1145/3661167.3661187
Oishwee SStakhanova NCodabux ZSpinellis DConstantinou EBacchelli A(2024)Large Language Model vs. Stack Overflow in Addressing Android Permission Related ChallengesProceedings of the 21st International Conference on Mining Software Repositories10.1145/3643991.3644933(373-383)Online publication date: 15-Apr-2024
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Mahmud TChe MRouijel JKhan MYang GRoychoudhury APaiva AAbreu RStorey M(2024)APICIA: An API Change Impact Analyzer for Android AppsProceedings of the 2024 IEEE/ACM 46th International Conference on Software Engineering: Companion Proceedings10.1145/3639478.3640041(99-103)Online publication date: 14-Apr-2024
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Barzolevskaia ABranca EStakhanova N(2024)Measuring and Characterizing (Mis)compliance of the Android Permission SystemIEEE Transactions on Software Engineering10.1109/TSE.2024.336292150:4(742-764)Online publication date: 12-Feb-2024
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Li SLi RYu YYan KYang SDiao W(2024)Understanding Android OS Forward Compatibility Support for Legacy Apps: A Data-Driven Analysis2024 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER)10.1109/SANER60148.2024.00029(216-226)Online publication date: 12-Mar-2024
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