Virtual Device Farms for Mobile App Testing at Scale: A Pursuit for Fidelity, Efficiency, and Accessibility

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Abstract

Virtual devices based on device emulation have been widely used in lab research of mobile app testing for their efficiency and low cost. However, it remains controversial to use virtual devices for app testing in industry, given the inherent difficulties of high-fidelity emulation across diverse mobile systems and devices. Hence, mobile app companies still rely on physical device farms or services like AWS Device Farm.This paper presents our effort to analyze, improve, and effectively use virtual devices for large-scale testing of mobile apps like Douyin. Our goal is to understand the fidelity of virtual devices and to explore how to better utilize virtual devices to improve the efficiency and accessibility of mobile app testing in industrial settings. Our study is conducted on a massive commercial testing infrastructure that deploys a physical device farm and its virtualized counterpart.We show that high-fidelity app testing can be achieved by sensible design and implementation of virtual device farms. With that, we find that major discrepancies are no longer caused by commonly believed factors like hardware heterogeneity and system customizations, but due to non-standard, uncoordinated, and occasionally defective vendor-specific services and drivers, as well as defense mechanisms against malicious app behavior. We present effective solutions to address those problems to significantly improve testing fidelity. We also share our experiences of using virtual device farms to substantially improve the efficiency and accessibility of mobile app testing, without compromising safety.

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APA

Lin, H., Qiu, J., Wang, H., Li, Z., Gong, L., Gao, D., … Xu, T. (2023). Virtual Device Farms for Mobile App Testing at Scale: A Pursuit for Fidelity, Efficiency, and Accessibility. In Proceedings of the Annual International Conference on Mobile Computing and Networking, MOBICOM (pp. 674–690). Association for Computing Machinery. https://doi.org/10.1145/3570361.3613259

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