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Are Mutation Scores Correlated with Real Fault Detection? A Large Scale Empirical Study on the Relationship Between Mutants and Real Faults

机译:突变评分是否与实际故障检测相关?突变与真实断层关系的大规模实证研究

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Empirical validation of software testing studies is increasingly relying on mutants. This practice is motivated by the strong correlation between mutant scores and real fault detection that is reported in the literature. In contrast, our study shows that correlations are the results of the confounding effects of the test suite size. In particular, we investigate the relation between two independent variables, mutation score and test suite size, with one dependent variable the detection of (real) faults. We use two data sets, CoreBench and De-fects4J, with large C and Java programs and real faults and provide evidence that all correlations between mutation scores and real fault detection are weak when controlling for test suite size. We also found that both independent variables significantly influence the dependent one, with significantly better fits, but overall with relative low prediction power. By measuring the fault detection capability of the top ranked, according to mutation score, test suites (opposed to randomly selected test suites of the same size), we found that achieving higher mutation scores improves significantly the fault detection. Taken together, our data suggest that mutants provide good guidance for improving the fault detection of test suites, but their correlation with fault detection are weak.
机译:软件测试研究的经验验证越来越依赖于突变体。这种做法是由文献中报道的突变体分数与实际故障检测之间的强相关性引起的。相反,我们的研究表明,相关性是测试套件大小的混杂影响的结果。特别是,我们调查了两个自变量之间的关系,即突变得分和测试套件大小,其中一个因变量用于检测(实际)故障。我们使用两个数据集CoreBench和De-fects4J,它们具有大型的C和Java程序以及真实的错误,并提供证据表明,在控制测试套件的大小时,变异评分和真实的错误检测之间的所有相关性都很弱。我们还发现,这两个自变量都显着影响因变量,具有显着更好的拟合度,但总体而言具有相对较低的预测能力。通过测量排名最高的故障检测能力(根据突变分数)和测试套件(与相同大小的随机选择的测试套件相对),我们发现获得更高的突变分数可以显着改善故障检测。综上所述,我们的数据表明,突变体为改进测试套件的故障检测提供了很好的指导,但它们与故障检测的相关性较弱。

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