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Exploring output-based coverage for testing PHP web applications

机译:探索基于输出的覆盖率测试PHP Web应用程序

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In software testing, different testers focus on different aspects of the software such as functionality, performance, design, and other attributes. While many tools and coverage metrics exist to support testers at the code level, not much support is targeted for testers who want to inspect the output of a program such as a dynamic web application. To support this category of testers, we propose a family of output-coverage metrics (similar to statement, branch, and path coverage metrics on code) that measure how much of the possible output has been produced by a test suite and what parts of the output are still uncovered. To do that, we first approximate the output universe using our existing symbolic execution technique. Then, given a set of test cases, we map the produced outputs onto the output universe to identify the covered and uncovered parts and compute output-coverage metrics. In our empirical evaluation on seven real-world PHP web applications, we show that selecting test cases by output coverage is more effective at identifying presentation faults such as HTML validation errors and spelling errors than selecting test cases by traditional code coverage. In addition, to help testers understand output coverage and augment test cases, we also develop a tool called WebTest that displays the output universe in one single web page and allows testers to visually explore covered and uncovered parts of the output.
机译:在软件测试中,不同的测试人员专注于功能,性能,设计和其他属性等软件的不同方面。虽然存在许多工具和覆盖度量来支持代码级别的测试仪,但对于想要检查动态Web应用程序等程序输出的测试人员,而不是很多支持。为了支持这类测试人员,我们提出了一系列输出覆盖度量(类似于代码上的语句,分支和路径覆盖度量标准),这些标准测量了测试套件和哪些部分的可能输出输出仍未覆盖。为此,我们首先使用现有的符号执行技术近似输出宇宙。然后,给定一组测试用例,我们将产生的输出映射到输出宇宙上,以识别所覆盖和未覆盖的零件和计算输出覆盖度量。在我们对七个现实世界PHP Web应用程序的实证评估中,我们显示通过输出覆盖的选择案例在识别出识别出现故障(如HTML验证错误和拼写错误)中,比通过传统代码覆盖选择测试用例,更有效。此外,为了帮助测试人员了解输出覆盖范围和增强测试用例,我们还开发一个名为WebTest的工具,它在一个网页中显示输出Universe,并允许测试人员在视觉上探索覆盖和未被覆盖的输出部分。

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