Brunel University Research Archive(BURA) preserves and enables easy and open access to all
types of digital content. It showcases Brunel's research outputs.
Research contained within BURA is open access, although some publications may be subject
to publisher imposed embargoes. All awarded PhD theses are also archived on BURA.
Browsing by Subject software defect prediction
Showing results 1 to 5 of 5
| Issue Date | Title | Author(s) |
|---|---|---|
| 15-Apr-2020 | Assessing software defection prediction performance: why using the Matthews correlation coefficient matters | Yao, J; Shepperd, M |
| 18-May-2018 | A Comprehensive Investigation of the Role of Imbalanced Learning for Software Defect Prediction | Song, Q; Guo, Y; Shepperd, M |
| 17-Jun-2021 | The impact of using biased performance metrics on software defect prediction research | Yao, J; Shepperd, M |
| 18-Jun-2024 | Improving classifier-based effort-aware software defect prediction by reducing ranking errors | Guo, Y; Shepperd, M; Li, N |
| 22-Feb-2020 | A systematic review of unsupervised learning techniques for software defect prediction | Li, N; Shepperd, M; Guo, Y |