research-article

What's inside my app?: understanding feature redundancy in mobile apps

Authors:

Xiangqun ChenAuthors Info & Claims

ICPC '18: Proceedings of the 26th Conference on Program Comprehension

Pages 266 - 276

https://doi.org/10.1145/3196321.3196329

Published: 28 May 2018 Publication History

Abstract

As the number of mobile apps increases rapidly, many users may install dozens of, or even hundreds of, apps on a single smartphone. However, many apps on the same phone may contain similar or even the same feature, resulting in feature redundancy. For example, multiple apps may check weather forecast for the user periodically. Feature redundancy may cause many undesirable side-effects such as consuming extra CPU resources and network traffic. This paper proposes a method to identify common features within an app, and evaluated it on over four thousand popular apps. Experiments on a list of apps installed on actual smartphones show that the extent of feature redundancy is very high. We found that more than 85% of user smartphones contain redundant features, while in extreme cases, some smartphones may contain dozens of apps with the same feature. In addition, our user surveys found out that about half of the redundant features are undesirable from the end users' perspective, which indicates that feature redundancy has become an important issue that needs to be investigated further.

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Cited By

Liu YMa YXiao XXie TLiu X(2023)LegoDroid: flexible Android app decomposition and instant installationScience China Information Sciences10.1007/s11432-021-3528-766:4Online publication date: 27-Mar-2023
https://doi.org/10.1007/s11432-021-3528-7
Velazquez-Rodriguez CConstantinou EDe Roover C(2022)Uncovering Library Features from API Usage on Stack Overflow2022 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER)10.1109/SANER53432.2022.00035(207-217)Online publication date: Mar-2022
https://doi.org/10.1109/SANER53432.2022.00035
Li YZhang ZLiu BYang ZLiu YCadar CZhang X(2021)ModelDiff: testing-based DNN similarity comparison for model reuse detectionProceedings of the 30th ACM SIGSOFT International Symposium on Software Testing and Analysis10.1145/3460319.3464816(139-151)Online publication date: 11-Jul-2021
https://dl.acm.org/doi/10.1145/3460319.3464816
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Published In

cover image ACM Conferences

ICPC '18: Proceedings of the 26th Conference on Program Comprehension

May 2018

423 pages

ISBN:9781450357142

DOI:10.1145/3196321

General Chair:
Foutse Khomh
École Polytechnique de Montréal, Canada
,
Program Chairs:
Chanchal K. Roy
University of Saskatchewan, Canada
,
Janet Siegmund
University of Passau, Germany

Copyright © 2018 ACM.

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: 28 May 2018

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National Key Research and Development Program
National Natural Science Foundation of China

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ICSE '18

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SIGSOFT
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ICSE '18: 40th International Conference on Software Engineering

May 28 - 29, 2018

Gothenburg, Sweden

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Cited By

Liu YMa YXiao XXie TLiu X(2023)LegoDroid: flexible Android app decomposition and instant installationScience China Information Sciences10.1007/s11432-021-3528-766:4Online publication date: 27-Mar-2023
https://doi.org/10.1007/s11432-021-3528-7
Velazquez-Rodriguez CConstantinou EDe Roover C(2022)Uncovering Library Features from API Usage on Stack Overflow2022 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER)10.1109/SANER53432.2022.00035(207-217)Online publication date: Mar-2022
https://doi.org/10.1109/SANER53432.2022.00035
Li YZhang ZLiu BYang ZLiu YCadar CZhang X(2021)ModelDiff: testing-based DNN similarity comparison for model reuse detectionProceedings of the 30th ACM SIGSOFT International Symposium on Software Testing and Analysis10.1145/3460319.3464816(139-151)Online publication date: 11-Jul-2021
https://dl.acm.org/doi/10.1145/3460319.3464816
Scoccia GMalavolta IAutili MDi Salle AInverardi P(2021)Enhancing Trustability of Android Applications via User-Centric Flexible PermissionsIEEE Transactions on Software Engineering10.1109/TSE.2019.294193647:10(2032-2051)Online publication date: 1-Oct-2021
https://doi.org/10.1109/TSE.2019.2941936
Scoccia G(2019)Automated Feature Identification for Android AppsSoftware Engineering and Formal Methods10.1007/978-3-030-57506-9_7(77-84)Online publication date: 16-Sep-2019
https://dl.acm.org/doi/10.1007/978-3-030-57506-9_7

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