Software quality estimation with limited fault data: a semi-supervised learning perspective

@article{Seliya2007SoftwareQE,
  title={Software quality estimation with limited fault data: a semi-supervised learning perspective},
  author={Naeem Seliya and Taghi M. Khoshgoftaar},
  journal={Software Quality Journal},
  year={2007},
  volume={15},
  pages={327-344}
}
We addresses the important problem of software quality analysis when there is limited software fault or fault-proneness data. A software quality model is typically trained using software measurement and fault data obtained from a previous release or similar project. Such an approach assumes that fault data is available for all the training modules. Various issues in software development may limit the availability of fault-proneness data for all the training modules. Consequently, the available… CONTINUE READING
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