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 Author Song, Q
Showing results 1 to 9 of 9
Issue Date | Title | Author(s) |
2008 | Can k-NN imputation improve the performance of C4.5 with small software project data sets? A comparative evaluation | Song, Q; Shepperd, MJ; Chen, X; Liu, J |
18-May-2018 | A Comprehensive Investigation of the Role of Imbalanced Learning for Software Defect Prediction | Song, Q; Guo, Y; Shepperd, M |
2013 | Data quality: Some comments on the NASA software defect datasets | Shepperd, M; Song, Q; Sun, Z; Mair, C |
2007 | A delay-dependent LMI approach to dynamics analysis of discrete-time recurrent neural networks with time-varying delays | Song, Q; Wang, Z |
2011 | A general software defect-proneness prediction framework | Song, Q; Jia, Z; Shepperd, M; Ying, S; Liu, J |
2009 | Integrate the GM(1,1) and Verhulst models to predict software stage effort | Wang, Y; Song, Q; MacDonell, S; Shepperd, M; Shen, J |
2011 | Predicting software project effort: A grey relational analysis based method | Song, Q; Shepperd, M |
2006 | Software Defect Association Mining and Defect Correction Effort Prediction | Song, Q; Shepperd, MJ; Cartwright, MH; Mair, C |
2008 | Stability analysis of impulsive stochastic Cohen–Grossberg neural networks with mixed time delays | Song, Q; Wang, Z |