A systematical study on application performance management libraries for apps

Tang, Y. , Wang, H., Zhan, X., Luo, X., Zhou, Y., Zhou, H., Yan, Q., Sui, Y. and Keung, J. (2022) A systematical study on application performance management libraries for apps. IEEE Transactions on Software Engineering, 48(8), pp. 3044-3065. (doi: 10.1109/TSE.2021.3077654)

Abstract

Being able to automatically detect the performance issues in apps can significantly improve apps’ quality as well as having a positive influence on user satisfaction. A pplication P erformance M anagement (APM) libraries are used to locate the apps’ performance bottleneck, monitor their behaviors at runtime, and identify potential security risks. Although app developers have been exploiting application performance management (APM) tools to capture these potential performance issues, most of them do not fully understand the internals of these APM tools and the effect on their apps. To fill this gap, in this paper, we conduct the first systematic study on APMs for apps by scrutinizing 25 widely-used APMs for Android apps and develop a framework named APMHunter for exploring the usage of APMs in Android apps. Using APMHunter, we conduct a large-scale empirical study on 500,000 Android apps to explore the usage patterns of APMs and discover the potential misuses of APMs. We obtain two major findings: 1) some APMs still employ deprecated permissions and approaches, which makes APMs fail to perform as expected; 2) inappropriate use of APMs can cause privacy leaks. Thus, our study suggests that both APM vendors and developers should design and use APMs scrupulously.

• Item Type: Articles
• Additional Information: This work was supported in part by ShanghaiTech Start-up Research under Grant 2020F0203-000-14, in part by Hong Kong RGC Projects under Grants 152223/17E, 152239/18E, and CityU C1008-16G, in part by the National Natural Science Foundation of China under Grant 62072046, in part by Leading Innovative and Entrepreneur Team Introduction Program of Zhejiang under Grant 2018R01005, and in part by the Fundamental Research Funds for the Central Universities under Grant K20200019.
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Tang, Dr Yutian
• Authors: Tang, Y., Wang, H., Zhan, X., Luo, X., Zhou, Y., Zhou, H., Yan, Q., Sui, Y., and Keung, J.
• College/School: College of Science and Engineering > School of Computing Science
• Journal Name: IEEE Transactions on Software Engineering
• Publisher: IEEE
• ISSN: 0098-5589
• ISSN (Online): 1939-3520
• Published Online: 05 May 2021