Dataset For Software Defect Predictions
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资源简介:
SOFTLAB: dataset were from a Turkish software company which develops embedded controllers for home appliances [1] <br>RELINK: Dataset with has 26 static code features and contains three projects (Apache HTTP Server (Apache), OpenIntents Safe (Safe), and ZXing) [2]<br>NASA: Dataset from e C-based and are extracted from a software system which is made of a set of static code features [3].<br>4. AEEEM: dataset was compiled by Marco et al. [4], and contains five open source projects with 5,371 data points. The projects include: Apache Lucene (LC), Equinox (EQ), Eclipse JDT Core (JDT), Eclipse PDE UI (PDE) and Mylyn (ML).<br><br>AEEEM software defect datasets which has a format of ARFF was collected by D’Ambros et al. [1]<br>[1] M. D’Ambros, M. Lanza, and R. Robbes, “Evaluating defect prediction approaches: A benchmark and an extensive comparison,”Empirical Softw. Engg., vol. 17, no. 4-5, pp. 531–577, Aug. 2012.<br>[3] ] B. Ghotra, S. McIntosh, and A. E. Hassan, “Revisiting the impact of classification techniques on the performance of defect prediction models,” in 2015 IEEE/ACM 37th IEEE International Conference on Software Engineering, vol. 1. IEEE, 2015, pp. 789–800.<br>[4] M. D’Ambros, M. Lanza, and R. Robbes, “Evaluating defect prediction approaches: a benchmark and an extensive comparison,” Empirical Software Engineering, vol. 17, no. 4, pp. 531–577, 2012
SOFTLAB数据集源自一家土耳其软件企业,该企业面向家用电器研发嵌入式控制器[1]
RELINK数据集包含26项静态代码特征,涵盖三个项目:Apache HTTP服务器(Apache)、OpenIntents Safe(Safe)以及ZXing[2]
NASA数据集基于C语言开发,从由若干静态代码特征构成的软件系统中提取得到[3]
4. AEEEM数据集由Marco等人于文献[4]中构建完成,包含5371条数据样本,涵盖五个开源项目:Apache Lucene(LC)、Equinox(EQ)、Eclipse JDT Core(JDT)、Eclipse PDE UI(PDE)以及Mylyn(ML)。
采用ARFF格式的AEEEM软件缺陷数据集由D’Ambros等人于文献[1]采集完成
[1] M. D’Ambros、M. Lanza与R. Robbes,《评估缺陷预测方法:基准测试与大规模对比》,《实证软件工程》,2012年8月,第17卷第4-5期,第531-577页
[3] B. Ghotra、S. McIntosh与A. E. Hassan,《重新审视分类技术对缺陷预测模型性能的影响》,收录于2015年IEEE/ACM第37届国际软件工程会议(第1卷),IEEE出版社,2015年,第789-800页
[4] M. D’Ambros、M. Lanza与R. Robbes,《评估缺陷预测方法:基准测试与大规模对比》,《实证软件工程》,2012年,第17卷第4期,第531-577页
提供机构:
figshare
创建时间:
2022-04-04
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数据集介绍

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