Towards Measuring Real-World Performance of Android Devices

In this paper we investigate how to measure real world performance of Android devices using app start durations. To this end we collect ground truth app start times using an automated mechanical setup. The ground truth start times are highly correlated with the outputs from Android's ActivityManager, which we then use to obtain app start times during normal use on a range of rooted devices. We then predict app start times with supervised learning to detect if device performance has changed over time. We show that training data can be gathered on a small set of rooted devices and then applied to other, non rooted devices. We also present an unsupervised method that can track the evolution of the system performance without requiring root access at all.