通过对执行配置文件进行聚类分析来查找故障

Proceedings of the 23rd International Conference on Software Engineering. ICSE 2001 Pub Date : 2001-07-01 DOI:10.1109/ICSE.2001.919107

William Dickinson, David Leon, Andy Podgurski

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引用次数: 308

摘要

我们通过实验评估了使用执行配置文件的聚类分析来发现由一组潜在测试用例引起的执行失败的有效性。我们比较了几种选择执行的过滤过程，以评估是否符合需求。每个过滤过程都涉及采样策略和聚类度量的选择。结果表明，基于聚类的过滤过程比简单的随机抽样更有效地识别操作执行总体中的失败，而从聚类中进行自适应抽样是最有效的抽样策略。结果还表明，为工业轮廓特征赋予额外权重的聚类指标是最有效的。通过多维缩放生成的执行种群散点图用于直观地了解这些结果。

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Finding failures by cluster analysis of execution profiles

We experimentally evaluate the effectiveness of using cluster analysis of execution profiles to find failures among the executions induced by a set of potential test cases. We compare several filtering procedures for selecting executions to evaluate for conformance to requirements. Each filtering procedure involves a choice of a sampling strategy and a clustering metric. The results suggest that filtering procedures based on clustering are more effective than simple random sampling for identifying failures in populations of operational executions, with adaptive sampling from clusters being the most effective sampling strategy. The results also suggest that clustering metrics that give extra weight to industrial profile features are most effective. Scatter plots of execution populations, produced by multidimensional scaling, are used to provide intuition for these results.

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Proceedings of the 23rd International Conference on Software Engineering. ICSE 2001

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