作为故障预测器的软件度量的增强

2015 Signal Processing: Algorithms, Architectures, Arrangements, and Applications (SPA) Pub Date : 2015-12-28 DOI:10.1109/SPA.2015.7365107

Nader Alexan, Hisham Othman, P. Montag

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引用次数: 2

摘要

从手机到医疗系统，软件已经成为我们身边几乎所有设备的一部分;这些设备的故障可能会造成致命的后果。因此，消除这些故障是不可避免的。本研究试图使用Pearson和Spearman相关系数在代码故障和软件度量之间找到相关性，目的是增强故障预测器。结果显示了软件度量和代码失败之间统计上显著的相关性。这项研究在测试与代码失败高度相关的指标组合方面是独一无二的。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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An enhancement of software metrics as failure predictors

Software has become a part of almost every device around us, from mobile phones to medical systems; Failure within such devices can have fatal consequences. Thus, the need for eliminating these failures is inevitable. This study attempts to find a correlation - using Pearson and Spearman correlation coefficients - between code failures and software metrics with the goal of enhancing failure predictors. The results show statistically significant correlations between software metrics and code failures. This study is unique in testing certain combinations of metrics that are highly correlated with code failures.

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来源期刊

2015 Signal Processing: Algorithms, Architectures, Arrangements, and Applications (SPA)

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