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Using Branch Frequency Spectra to Evaluate Operational Coverage

机译：使用分支频谱评估运行范围

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摘要

Coverage metrics try to quantify how well a software artifact is tested. High coverage numbers instill confidence in the software and might even be necessary to obtain certification. Unfortunately, achieving high coverage numbers does not imply high quality of the test suite. One shortcoming is that coverage metrics do not measure how well test suites cover systems in production. We look at coverage from an operational perspective. We evaluate test suite quality by comparing runs executed during testing with runs executed in production. Branch frequency spectra are employed to capture the behavior during runtime. Differences in the branch frequency spectra between field executions and testing runs indicate test suite deficiencies. This post-release test suite quality assurance mechanism can be used to (1) build confidence by pooling coverage information from many execution sites and (2) guide test suite augmentation in order to prepare the test suite for the next release cycle.
机译：覆盖率指标试图量化对软件工件的测试程度。高覆盖率的数字使人们对软件充满信心，甚至可能需要获得认证。不幸的是，获得高覆盖率并不意味着测试套件的高质量。缺点之一是覆盖率指标无法衡量测试套件覆盖生产系统的程度。我们从运营的角度来看范围。我们通过比较测试期间执行的运行与生产中执行的运行来评估测试套件的质量。使用分支频谱来捕获运行时的行为。现场执行和测试运行之间的分支频谱差异表明测试套件存在缺陷。此发布后测试套件质量保证机制可用于（1）通过合并来自许多执行站点的覆盖信息来建立信心，以及（2）指导测试套件扩充，以便为下一个发布周期准备测试套件。

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