系统地测试和诊断Android应用程序的响应性

Wenhua Zhao, Zhenkai Ding, Mingyuan Xia, Zhengwei Qi
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引用次数: 6

摘要

从用户的角度来看,应用响应性是对应用性能最直观的诠释。传统的性能分析器只关注一种程序活动(例如,CPU分析),而导致响应速度慢的原因是多种多样的,甚至是多种因素共同作用的结果。此外,各种测试配置(如设备硬件和无线连接)可能对特定程序活动产生巨大影响,并间接影响应用程序的响应性。传统的移动测试缺乏揭示配置敏感漏洞的机制。在本文中,我们提出了AppSPIN,一个自动诊断应用程序响应错误和系统地探索配置敏感错误的工具。AppSPIN检测应用程序来收集程序事件和UI响应性。仪器化的应用程序使用自动猴子测试器进行测试,AppSPIN将过多和冗长的程序事件与运行时检测到的不良响应关联起来。诊断过程还综合了应用程序的主要资源瓶颈。在一次测试运行后,AppSPIN自动将测试配置更改为使用大多数瓶颈资源,以进一步探索仅在特定测试配置下发生的响应性错误。我们对30个真实应用的初步实验表明,AppSPIN可以检测出123个响应性错误,并在平均15分钟的测试时间内成功诊断出87%的原因。另外,通过改变测试配置,AppSPIN在4个额外的测试运行中发现了大量的新bug。
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Systematically Testing and Diagnosing Responsiveness for Android Apps
App responsiveness is the most intuitive interpretation of app performance from user's perspective. Traditional performance profilers only focus on one kind of program activities (e.g., CPU profiling), while the cause for slow responsiveness is diverse or even due to the joint effect of multiple kinds. Also, various test configurations, such as device hardware and wireless connectivity can have dramatic impact on particular program activities and indirectly affect app responsiveness. Conventional mobile testing lacks mechanisms to reveal configuration-sensitive bugs. In this paper, we propose AppSPIN, a tool to automatically diagnose app responsiveness bugs and systematically explore configuration-sensitive bugs. AppSPIN instruments the app to collect program events and UI responsiveness. The instrumented app is exercised with automated monkey testers and AppSPIN correlates excessive and lengthy program events with bad responsiveness detected at runtime. The diagnosis process also synthesizes the major resource bottleneck for the app. After one test run, AppSPIN automatically alters the test configuration to with most bottlenecked resource to further explore responsiveness bugs happened only with particular test configurations. Our preliminary experiments with 30 real-world apps show that AppSPIN can detect 123 responsiveness bugs and successfully diagnose the cause for 87% cases, within an average of 15-minute test time. Also with altered test configurations, AppSPIN uncovers a notable number of new bugs within four extra test runs.
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