Automated Measurement and Change Detection of an Application’s Network Activity for Quality Assistance
Robert Nissa Holmgren · 2014
Network usage is an important quality metric for mobile apps. Slow networks, low monthly traffic quotas and high roaming fees restrict mobile users’ amount of usable Internet traffic. Companies wanting their apps to stay competitive must be aware of their network usage and changes to it.Short feedback loops for the impact of code changes are key in agile software development. To notify stakeholders of changes when they happen without being prohibitively expensive in terms of manpower the change detection must be fully automated. To further decrease the manpower overhead cost of implementing network usage change detection the system need to have low configuration requirements, and keep the false positive rate low while managing to detect larger changes.This thesis proposes an automated change detection method for network activity to quickly notify stakeholders with relevant information to begin a root cause analysis after a change in the network activity is introduced. With measurements of the Spotify’s iOS app we show that the tool achieves a low rate of false positives while detecting relevant changes in the network activity even for apps with dynamic network usage patterns as Spotify.