测试覆盖率和可靠性之间的关系

Y. Malaiya, Michael Naixin Li, J. Bieman, R. Karcich, Bob Skibbe
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引用次数: 115

摘要

对测试工作、覆盖率和可靠性之间的关系进行建模,并提出一个将测试工作与测试覆盖率联系起来的对数模型:语句(或块)覆盖率、分支(或决策)覆盖率、计算使用(c-use)覆盖率,或谓词使用(p-use)覆盖率。该模型基于一个假设,即任何覆盖度量的可枚举对象(如分支或块)都具有不同的可检测性,就像单个缺陷一样。这个模型允许我们将测试覆盖度量直接与缺陷覆盖联系起来。使用具有实际缺陷的程序的数据集来验证模型。结果与已知的块、分支和p-use覆盖测度之间的包含关系一致。我们将展示缺陷密度如何控制到下一次故障的时间。该模型可以消除诸如测试应用程序策略之类的变量。它适用于高可靠性应用,其中自动(或手动)测试生成用于覆盖尚未测试的可再生材料。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The relationship between test coverage and reliability
Models the relationship between testing effort, coverage and reliability, and presents a logarithmic model that relates testing effort to test coverage: statement (or block) coverage, branch (or decision) coverage, computation use (c-use) coverage, or predicate use (p-use) coverage. The model is based on the hypothesis that the enumerables (like branches or blocks) for any coverage measure have different detectability, just like the individual defects. This model allows us to relate a test coverage measure directly to the defect coverage. Data sets for programs with real defects are used to validate the model. The results are consistent with the known inclusion relationships among block, branch and p-use coverage measures. We show how the defect density controls the time-to-next-failure. The model can eliminate variables like the test application strategy from consideration. It is suitable for high-reliability applications where automatic (or manual) test generation is used to cover enemerables which have not yet been tested.<>
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