.png){kind=icon}
.png){kind=icon}
Return
A Systematical Study on Application Performance Management Libraries for Apps
.png){kind=icon}
OA
AI
DOI：10.1109/TSE.2021.3077654.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
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. Application Performance Management (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.
Keywords:
Privacy
Systematics
Runtime
Prototypes
Libraries
Internet
Behavioral sciences
Empirical study
android
application performance management
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
5.6
Papers:
2.8K
Citations:
1.1W
View more organizations