Current metrics for assessing the adequacy of a test-suite plainly focus on the number of components (be it lines, branches, paths) covered by the suite, but do not explicitly check how the tests actually exercise these components and whether they provide enough information so that spectrum-based fault localization techniques can perform accurate fault isolation. We propose a metric, called, aimed at complementing adequacy measurements by quantifying a test-suite's diagnosability, i.e., the effectiveness of applying spectrum-based fault localization to pinpoint faults in the code in the event of test failures. Our aim is to increase the value generated by creating thorough test-suites, so they are not only regarded as error detection mechanisms but also as effective diagnostic aids that help widely-used fault-localization techniques to accurately pinpoint the location of bugs in the system. We have performed a topology-based simulation of thousands of spectra and have found that DDU can effectively establish an upper bound on the effort to diagnose faults. Furthermore, our empirical experiments using the Defects4J dataset show that optimizing a test suite with respect to DDU yields a 34% gain in spectrum-based fault localization report accuracy when compared to the standard branch-coverage metric.

中文翻译：

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节目谱可诊断性的理论和实证分析

当前用于评估测试套件充分性的指标明确关注套件所涵盖的组件（行、分支、路径）的数量，但并未明确检查测试如何实际使用这些组件以及它们是否提供足够的信息以便基于频谱的故障定位技术可以进行准确的故障隔离。我们提出了一个度量，称为，旨在通过量化测试套件的可诊断性来补充充分性测量，即在测试失败的情况下应用基于频谱的故障定位来查明代码中的故障的有效性。我们的目标是通过创建完整的测试套件来增加产生的价值，因此，它们不仅被视为错误检测机制，而且被视为有效的诊断辅助工具，可帮助广泛使用的故障定位技术准确定位系统中的错误位置。我们对数以千计的光谱进行了基于拓扑的模拟，并发现 DDU 可以有效地建立故障诊断努力的上限。此外，我们使用 Defects4J 数据集的实证实验表明，与标准分支覆盖度量相比，优化与 DDU 相关的测试套件可使基于频谱的故障定位报告准确性提高 34%。