NChecker: saving mobile app developers from network disruptions

Xinxin Jin, Peng Huang, Tianyin Xu, Yuanyuan Zhou
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引用次数: 12

Abstract

Most of today's mobile apps rely on the underlying networks to deliver key functions such as web browsing, file synchronization, and social networking. Compared to desktop-based networks, mobile networks are much more dynamic with frequent connectivity disruptions, network type switches, and quality changes, posing unique programming challenges for mobile app developers. As revealed in this paper, many mobile app developers fail to handle these intermittent network conditions in the mobile network programming. Consequently, network programming defects (NPDs) are pervasive in mobile apps, causing bad user experiences such as crashes, data loss, etc. Despite the development of network libraries in the hope of lifting the developers' burden, we observe that many app developers fail to use these libraries properly and still introduce NPDs. In this paper, we study the characteristics of the real-world NPDs in Android apps towards a deep understanding of their impacts, root causes, and code patterns. Driven by the study, we build NChecker, a practical tool to detect NPDs by statically analyzing Android app binaries. NChecker has been applied to hundreds of real Android apps and detected 4180 NPDs from 285 randomly-selected apps with a 94+% accuracy. Our further analysis of these defects reveals the common mistakes of app developers in working with the existing network libraries' abstractions, which provide insights for improving the usability of mobile network libraries.
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NChecker:将移动应用开发者从网络中断中解救出来
今天的大多数移动应用程序都依赖底层网络来提供关键功能,如网页浏览、文件同步和社交网络。与基于桌面的网络相比,移动网络更加动态,频繁出现连接中断、网络类型切换和质量变化,给移动应用开发者带来了独特的编程挑战。正如本文所揭示的,许多移动应用程序开发人员在移动网络编程中没有处理好这些间歇性的网络情况。因此,网络编程缺陷(network programming defects, npd)在移动应用中普遍存在,导致崩溃、数据丢失等不良用户体验。尽管网络库的发展希望减轻开发者的负担,但我们观察到许多应用开发者没有正确使用这些库,仍然引入npd。在本文中,我们研究了现实世界中Android应用中npd的特征,以深入了解其影响,根本原因和代码模式。在这项研究的推动下,我们构建了NChecker,这是一个通过静态分析Android应用程序二进制文件来检测npd的实用工具。NChecker已经应用于数百个真实的Android应用程序,并从285个随机选择的应用程序中检测出4180个npd,准确率为94%以上。我们对这些缺陷的进一步分析揭示了应用程序开发人员在使用现有网络库抽象时的常见错误,为提高移动网络库的可用性提供了见解。
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EuroSys '22: Seventeenth European Conference on Computer Systems, Rennes, France, April 5 - 8, 2022 EuroSys '21: Sixteenth European Conference on Computer Systems, Online Event, United Kingdom, April 26-28, 2021 EuroSys '20: Fifteenth EuroSys Conference 2020, Heraklion, Greece, April 27-30, 2020 STRADS: a distributed framework for scheduled model parallel machine learning NChecker: saving mobile app developers from network disruptions
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