Automated Visual Testing for Mobile Apps in an Industrial Setting


User Interface (UI) testing has become a common practice for quality assurance of industrial mobile applications (in short as apps). While many automated tools have been developed, they often do not satisfy two major industrial requirements that make a tool desirable in industrial settings: high applicability across platforms (eg, Android, iOS, AliOS, and Harmony OS) and high capability to handle apps with non-standard UI elements (whose internal structures cannot be acquired using platform APIs). Toward addressing these industrial requirements, automated visual testing emerges to take only device screenshots as input in order to support automated test generation. In this paper, we report our experiences of developing and deploying VTest, our industrial visual testing framework to assure high quality of Taobao, a highly popular industrial app with about one billion monthly active users. VTest includes carefully designed techniques and infrastructure support, outperforming Monkey (which has been popularly deployed in industry and shown to perform superiorly or similarly compared to state-of-the-art tools) with 87.6% more activity coverage. VTest has been deployed both internally in Alibaba and externally in the Software Green Alliance to provide testing services for top smartphone vendors and app vendors in China. We summarize five major lessons learned from developing and deploying VTest.

IEEE/ACM 44th International Conference on Software Engineering
Dezhi Ran
Dezhi Ran
Ph.D. student

My research interests include software engineering, programming language, and reinforcement learning.