Combatting Energy Issues for Mobile Applications

Author:

Li Xueliang1ORCID,Chen Junyang2,Liu Yepang3,Wu Kaishun2,Gallagher John P.4

Affiliation:

1. Research Institute of Trustworthy Autonomous Systems, Southern University of Science and Technology, Shenzhen, China

2. College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China

3. Research Institute of Trustworthy Autonomous Systems, Guangdong Provincial Key Laboratory of Brain-inspired Intelligent Computation, and Department of Computer Science and Engineering, Southern University of Science and Technology, China

4. Department of People and Technology, Roskilde University, and IMDEA Software Institute, Madrid, Spain

Abstract

Energy efficiency is an important criterion to judge the quality of mobile apps, but one third of our arbitrarily sampled apps suffer from energy issues that can quickly drain battery power. To understand these issues, we conduct an empirical study on 36 well-maintained apps such as Chrome and Firefox, whose issue tracking systems are publicly accessible. Our study involves issue causes, manifestation, fixing efforts, detection techniques, reasons of no-fixes, and debugging techniques. Inspired by the empirical study, we propose a novel testing framework for detecting energy issues in real-world mobile apps. Our framework examines apps with well-designed input sequences and runtime context. We develop leading edge technologies, e.g., pre-designing input sequences with potential energy overuse and tuning tests on-the-fly, to achieve high efficacy in detecting energy issues. A large-scale evaluation shows that 90.4% of the detected issues in our experiments were previously unknown to developers. On average, these issues can double the energy consumption of the test cases where the issues were detected. And our test achieves a low number of false positives. Finally, we show how our test reports can help developers fix the issues.

Funder

National Natural Science Foundation of China

Open Research Fund from Guangdong Laboratory of Artificial Intelligence and Digital Economy

Guandong Basic and Applied Basic Research Fundation

Guangdong Provincial Key Laboratory

Publisher

Association for Computing Machinery (ACM)

Subject

Software

Reference90 articles.

1. [n.d.]. ADB . Retrieved on 13 July 2022 from https://developer.android.com/topic/performance/power/setup-battery-historian.

2. [n.d.]. Battery monitor widget . Retrieved on 13 July 2022 from https://play.google.com/store/apps/details?id=com.fsinib.batterymonitor.

3. [n.d.]. Better battery stats . Retrieved on 13 July 2022 from https://f-droid.org/packages/com.asksven.betterbatterystats/.

4. [n.d.]. GDB . Retrieved from sourceware.org/gdb/onlinedocs/gdb/Backtrace.html.

5. [n.d.]. How Many Test Users in a Usability Study? Retrieved 13 July 2022 from https://www.nngroup.com/articles/how-many-test-users/.

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A large-scale empirical study on mobile performance: energy, run-time and memory;Empirical Software Engineering;2023-12-27

2. E-MANAFA: Energy Monitoring and ANAlysis tool For Android;Proceedings of the 37th IEEE/ACM International Conference on Automated Software Engineering;2022-10-10

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