A Systematical Study on Application Performance Management Libraries for Apps

  • Yutian Tang
  • , Haoyu Wang
  • , Xian Zhan
  • , Xiapu Luo
  • , Yajin Zhou
  • , Hao Zhou
  • , Qiben Yan
  • , Yulei Sui
  • , Jacky Wai Keung

Research output: Journal article publicationJournal articleAcademic researchpeer-review

6 Citations (Scopus)

Abstract

Being able to automatically detect the performance issues in apps will significantly improve their quality as well as having a positive influence on user satisfaction. 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, such as security risks, etc. 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 inAndroid apps. Using APMHunter, we conduct a large-scale empirical study on 500,000 Android apps to explore the usage patterns ofAPMs and discover the potential misuses of APMs. We obtain two major findings: 1) some APMs still employ deprecated permissions and approaches, which leads to APM malfunction as expected; 2) inappropriate APMs utilization will cause privacy leakages. Thus, our study suggests that both APM vendors and developers should design and use APMs scrupulously

Original languageEnglish
Pages (from-to)3044 - 3065
JournalIEEE Transactions on Software Engineering
Volume48
Issue number8
Early online date5 May 2021
DOIs
Publication statusPublished - 1 Aug 2022

ASJC Scopus subject areas

  • Software

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