Identifying Coincidental Correctness for Effective Fault Localization

CAO He-ling; JIANG Shu-juan; WANG Xing-ya; XUE Meng; QIAN Jun-yan

doi:10.3969/j.issn.0372-2112.2016.12.030

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Identifying Coincidental Correctness for Effective Fault Localization

更新时间：2025-07-16

- Identifying Coincidental Correctness for Effective Fault Localization
- Acta Electronica Sinica Vol. 44, Issue 12, Pages: 3026-3031(2016)
- 作者机构：
  
  1. 中国矿业大学计算机科学与技术学院,江苏,徐州,221116
  2. 河南工业大学信息科学与工程学院,河南,郑州,450001
  3. 桂林电子科技大学广西可信软件重点实验室,广西,桂林,541004
  4. 中国矿业大学计算机科学与技术学院,江苏,徐州,221116
  5. 河南工业大学信息科学与工程学院,河南,郑州,450001
  6. 桂林电子科技大学广西可信软件重点实验室,广西,桂林,541004
- 作者简介：
- 基金信息：
  
  National Natural Science Foundation of China (No.61202006, No.61340037, No.61502497, No.61562015, No.61602154);Research Project of Guangxi Key Laboratory of Trusted Software (No.kx201616, No.kx201532);Key Scientific Research Programs of colleges and universities of Henan Province (No.16A520005)
- DOI：10.3969/j.issn.0372-2112.2016.12.030
  CLC： TP311
- Published：2016
- 稿件说明：
移动端阅览
CAO He-ling, JIANG Shu-juan, WANG Xing-ya, et al. Identifying Coincidental Correctness for Effective Fault Localization[J]. Acta Electronica Sinica, 2016, 44(12): 3026-3031.
DOI：

CAO He-ling, JIANG Shu-juan, WANG Xing-ya, et al. Identifying Coincidental Correctness for Effective Fault Localization[J]. Acta Electronica Sinica, 2016, 44(12): 3026-3031. DOI： 10.3969/j.issn.0372-2112.2016.12.030.

摘要

错误定位是软件调试中耗时费力的活动之一.针对偶然正确性影响错误定位效率的问题，提出面向错误定位的偶然正确性识别方法.该方法首先识别偶然正确性元素；然后，挑选偶然正确性特征元素，使用该特征元素约简程序执行轨迹；在此基础上，建立基于模糊

均值聚类的偶然正确性识别模型，将其结果应用于错误定位.为验证该方法的有效性，基于3组测试程序开展偶然正确性识别，并将其结果应用于Tarantula等4种错误定位方法.实验结果表明，与基于

-means聚类的偶然正确性识别方法相比，该方法在偶然正确性识别方面具有较低的误报率和漏报率，并且更能提高错误定位的效率.

Abstract

Fault localization is one of the most time-consuming activities in software debugging.An identifying coincidental correctness approach for effective fault localization is proposed to decrease the effect of coincidental correctness on the effectiveness of fault localization.First

the elements of coincidental correctness are computed.Second

the higher suspicious coincidental correctness elements are selected as feature elements of coincidental correctness

and then program execution traces are reduced in terms of feature elements.Finally

fuzzy

-means based coincidental correctness identification model is created based on the reduced execution traces to locate faults.It was applied to analyze three groups of programs

d test cases removing coincidental correctness were used as input for four popular fault localization approaches

such as Tarantula.The experimental results show that our approach had low false positives and false negatives

and performed well in terms of the effectiveness.

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