When | What |
---|---|
February 2, 2016 | Updating BibTeX |
Nov 2011 | Dataset has been cleaned by MartinShepperd et al. (pc4’ and pc4’’ are the cleaned versions) |
December 2, 2004 | Donated by Tim Menzies |
This is one of the NASA Metrics Data Program defect data sets.
“How Good is Your Blind Spot Sampling Policy?” Available from http://menzies.us/pdf/03blind.pdf.
@INPROCEEDINGS{1281737,
author={Menzies, T. and Di Stefano, J.S.},
booktitle={High Assurance Systems Engineering, 2004. Proceedings. Eighth IEEE International Symposium on},
title={How good is your blind spot sampling policy},
year={2004},
pages={129-138},
keywords={formal specification;program verification;sampling methods;software metrics;automatic formal methods;black box probing;blind spot sampling;
defect detectors;formal specification;public domain defect data;software assessment;Aerospace engineering;Computer science;Costs;
Detectors;Mission critical systems;NASA;Project management;Proposals;Sampling methods;Systems engineering and theory},
doi={10.1109/HASE.2004.1281737},
ISSN={1530-2059},
month={March},}
@ARTICLE{6464273,
author={Shepperd, M. and Qinbao Song and Zhongbin Sun and Mair, C.},
journal={Software Engineering, IEEE Transactions on},
title={Data Quality: Some Comments on the NASA Software Defect Datasets},
year={2013},
volume={39},
number={9},
pages={1208-1215},
keywords={data analysis;learning (artificial intelligence);pattern classification;software reliability;IEEE Transactions on Software Engineering;
NASA software defect dataset;National Aeronautics and Space Administration;data preprocessing;data quality;data replication;
dataset provenance;defect-prone classification;machine learning;not-defect-prone classification;
software module classification;Abstracts;Communities;Educational institutions;NASA;PROM;Software;Sun;Empirical software engineering;
data quality;defect prediction;machine learning},
doi={10.1109/TSE.2013.11},
ISSN={0098-5589},
month={Sept},}