在不利条件下系统执行Android测试套件

Christoffer Quist Adamsen, Gianluca Mezzetti, Anders Møller
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引用次数: 97

摘要

事件驱动的应用程序,如移动应用程序,很难进行彻底的测试。应用程序程序员经常投入大量精力编写端到端测试套件。尽管这样的测试通常对源代码有很高的覆盖率,但我们发现它们通常关注于预期的行为,而不是异常事件的发生。另一方面,自动化测试工具可能能够更系统地探索状态空间,但这主要是在不了解单个应用程序的预期行为的情况下进行的。因此,许多编程错误在用户遇到之前是不会被注意到的。我们提出了一种新的测试方法,通过利用现有的测试套件,使得每个测试用例系统地暴露在不利的条件下,其中某些意外事件可能会干扰执行。通过这种方式,我们探索有趣的执行路径,并利用手动编写的测试套件中的断言,同时确保注入的事件不会影响预期的结果。我们面临的主要挑战是如何系统而有效地完成这一任务。我们通过在Android上实现一个工具Thor来评估这种方法。使用现有测试套件对四个实际应用程序进行测试的结果表明,相对于某些意外事件,应用程序通常是脆弱的,而我们的方法有效地提高了测试质量:在507个单独测试中,429个测试在暴露于不利条件时失败,这揭示了66个不同的问题,这些问题是通过常规测试执行无法检测到的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Systematic execution of Android test suites in adverse conditions
Event-driven applications, such as, mobile apps, are difficult to test thoroughly. The application programmers often put significant effort into writing end-to-end test suites. Even though such tests often have high coverage of the source code, we find that they often focus on the expected behavior, not on occurrences of unusual events. On the other hand, automated testing tools may be capable of exploring the state space more systematically, but this is mostly without knowledge of the intended behavior of the individual applications. As a consequence, many programming errors remain unnoticed until they are encountered by the users. We propose a new methodology for testing by leveraging existing test suites such that each test case is systematically exposed to adverse conditions where certain unexpected events may interfere with the execution. In this way, we explore the interesting execution paths and take advantage of the assertions in the manually written test suite, while ensuring that the injected events do not affect the expected outcome. The main challenge that we address is how to accomplish this systematically and efficiently. We have evaluated the approach by implementing a tool, Thor, working on Android. The results on four real-world apps with existing test suites demonstrate that apps are often fragile with respect to certain unexpected events and that our methodology effectively increases the testing quality: Of 507 individual tests, 429 fail when exposed to adverse conditions, which reveals 66 distinct problems that are not detected by ordinary execution of the tests.
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