TY - GEN
T1 - An Empirical Study to Identify Software Aging Indicators for Android OS
AU - Chen, Yulei
AU - Nie, Yuge
AU - Yin, Beibei
AU - Zheng, Zheng
AU - Wu, Huayao
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Android mobile devices have been suffering from performance degradation and increased failure rates during long-term operation, known as software aging. With the major changes in performance optimization and resource management in Android, it is spotted that the aging behavior of Android devices in the 2020s differs significantly from previous studies in resource utilization and performance metrics, which makes some classic metrics difficult to measure aging well, and new metrics are required to better describe the new phenomenon. Thus, we propose thread- and interface-level metrics to portray aging at a finer granularity and conduct an empirical study to reidentify classic and new software aging metrics in Android. Analysis confirms that software aging in Android is less reflected in global resources metrics but in more fine-grained ones, so thread- and interface-level metrics combined with specific classic resource and process-level metrics are helpful as indicators of software aging. These metrics have been confirmed and deployed for aging monitoring by our mobile phone manufacturer collaborators. A new experimental method customized for metric studies has also been adopted in this paper, significantly reducing data costs and interference in measurements.
AB - Android mobile devices have been suffering from performance degradation and increased failure rates during long-term operation, known as software aging. With the major changes in performance optimization and resource management in Android, it is spotted that the aging behavior of Android devices in the 2020s differs significantly from previous studies in resource utilization and performance metrics, which makes some classic metrics difficult to measure aging well, and new metrics are required to better describe the new phenomenon. Thus, we propose thread- and interface-level metrics to portray aging at a finer granularity and conduct an empirical study to reidentify classic and new software aging metrics in Android. Analysis confirms that software aging in Android is less reflected in global resources metrics but in more fine-grained ones, so thread- and interface-level metrics combined with specific classic resource and process-level metrics are helpful as indicators of software aging. These metrics have been confirmed and deployed for aging monitoring by our mobile phone manufacturer collaborators. A new experimental method customized for metric studies has also been adopted in this paper, significantly reducing data costs and interference in measurements.
KW - Android OS
KW - aging indicators
KW - software aging
KW - software reliability
UR - https://www.scopus.com/pages/publications/85175517660
U2 - 10.1109/QRS60937.2023.00049
DO - 10.1109/QRS60937.2023.00049
M3 - 会议稿件
AN - SCOPUS:85175517660
T3 - IEEE International Conference on Software Quality, Reliability and Security, QRS
SP - 428
EP - 439
BT - Proceedings - 2023 IEEE 23rd International Conference on Software Quality, Reliability, and Security, QRS 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 23rd IEEE International Conference on Software Quality, Reliability, and Security, QRS 2023
Y2 - 22 October 2023 through 26 October 2023
ER -