Data Quality: Some Comments on the NASA Software Defect Datasets

@article{Shepperd2013DataQS,
  title={Data Quality: Some Comments on the NASA Software Defect Datasets},
  author={Martin J. Shepperd and Qinbao Song and Zhongbin Sun and Carolyn Mair},
  journal={IEEE Transactions on Software Engineering},
  year={2013},
  volume={39},
  pages={1208-1215}
}
Background--Self-evidently empirical analyses rely upon the quality of their data. Likewise, replications rely upon accurate reporting and using the same rather than similar versions of datasets. In recent years, there has been much interest in using machine learners to classify software modules into defect-prone and not defect-prone categories. The publicly available NASA datasets have been extensively used as part of this research. Objective--This short note investigates the extent to which… CONTINUE READING
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The Scientific Method in Practice: Reproducibility in the Computational Sciences

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MIT Sloan School Working Paper 4773-10, 2010. http://ssm.com/abstract=1550193, Aug. 2012. 1214 IEEE TRANSACTIONS ON SOFTWARE ENGINEERING, VOL. 39, NO. 9, SEPTEMBER 2013 • 2010
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