Mitigating the Effect of Coincidental Correctness in Spectrum Based Fault Localization
Mitigating the Effect of Coincidental Correctness in Spectrum Based Fault Localization
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DOI：
10.1109/icst.2012.130
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发表时间：
2012-04
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通讯作者：
A. Bandyopadhyay
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作者：
A. Bandyopadhyay
巧合正确的测试用例是那些执行错误语句但不导致失败的测试用例。这样的测试用例降低了基于频谱的故障定位技术，如Ochiai的有效性。这些技术计算每个陈述的可疑分数。可疑性得分估计如果执行语句，程序将失败的可能性。碰巧正确的测试用例的存在降低了错误语句的可疑分数，从而降低了故障定位的有效性。我们提出了两种方法，预测巧合正确的测试用例，并使用预测，以提高基于频谱的故障定位的有效性。在第一种方法中，我们为通过的测试用例分配权重，使得可能巧合正确的测试用例获得较低的权重。然后我们使用权重来计算可疑分数。在第二种方法中，我们迭代地预测和删除巧合正确的测试用例，并计算可疑分数与减少的测试套件。在这篇论文中，我们调查的成本和有效性，我们的方法来预测巧合正确的测试用例，并利用预测。我们报告的结果，我们的初步评估的有效性和概述我们的研究计划。
Coincidentally correct test cases are those that execute faulty statements but do not cause failures. Such test cases reduce the effectiveness of spectrum-based fault localization techniques, such as Ochiai. These techniques calculate a suspiciousness score for each statement. The suspiciousness score estimates the likelihood that the program will fail if the statement is executed. The presence of coincidentally correct test cases reduces the suspiciousness score of the faulty statement, thereby reducing the effectiveness of fault localization. We present two approaches that predict coincidentally correct test cases and use the predictions to improve the effectiveness of spectrum based fault localization. In the first approach, we assign weights to passing test cases such that the test cases that are likely to be coincidentally correct obtain low weights. Then we use the weights to calculate suspiciousness scores. In the second approach, we iteratively predict and remove coincidentally correct test cases, and calculate the suspiciousness scores with the reduced test suite. In this dissertation, we investigate the cost and effectiveness of our approach to predicting coincidentally correct test cases and utilizing the predictions. We report the results of our preliminary evaluation of effectiveness and outline our research plan.