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Artifact for MobiCom'23: Virtual Device Farms for Mobile App Testing at Scale: A Pursuit for Fidelity, Efficiency, and Accessibility

Authors: Hao Lin; Jiaxing Qiu; Hongyi Wang; Zhenhua Li; Liangyi Gong; Di Gao; Yunhao Liu; +4 Authors

Artifact for MobiCom'23: Virtual Device Farms for Mobile App Testing at Scale: A Pursuit for Fidelity, Efficiency, and Accessibility

Abstract

This dataset contains the anonymized failure data collected from our physical and device farms over a three-month period. The failure data involves 5,918 physical devices as well as 5,918 virtualized devices running on ARM commodity servers. For more details, please visit our website (Android-Emulation-Testing.github.io) or read our paper: [MobiCom'23] Virtual Device Farms for Mobile App Testing at Scale: A Pursuit for Fidelity, Efficiency, and Accessibility If you use our dataset in your work, please reference it using: @inproceedings {lin2022virtual, author = {Lin, Hao and Qiu, Jiaxing and Wang, Hongyi and Li, Zhenhua and Gong, Liangyi and Gao, Di and Liu, Yunhao and Qian, Feng and Zhang, Zhao and Yang, Ping and Xu, Tianyin}, title = {{Virtual Device Farms for Mobile App Testing at Scale: A Pursuit for Fidelity, Efficiency, and Accessibility}}, booktitle = {The 29th Annual International Conference on Mobile Computing and Networking (ACM MobiCom'23)}, year = {2023}, publisher = {ACM} }

Version 1.0.2: This update adds reference information and fixes Colab icon issues.

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Keywords

Mobile App Testing, Virtualization, Fidelity, Efficiency

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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