[1] BAGGEN R, CORREIA J P, SCHILL K, et al. Standardized code quality benchmarking for improving software maintainability [J]. Software Quality Journal, 2012, 20(2): 287-307. [2] SHEPPERD M, SONG Q, SUN Z, et al. Data quality: some comments on the nasa software defect datasets [J]. IEEE Transactions on Software Engineering, 2013, 39(9): 1208-1215. [3] MA Y, LUO G, ZENG X, et al. Transfer learning for cross-company software defect prediction [J]. Information and Software Technology, 2012, 54(3): 248-256. [4] WANG S, YAO X. Using class imbalance learning for software defect prediction [J]. IEEE Transactions on Reliability, 2013, 62(2): 434-443. [5] SONG Q, JIA Z, SHEPPERD M, et al. A general software defect-proneness prediction framework [J]. IEEE Transactions on Software Engineering, 2011, 37(3): 356-370. [6] PENG Y, KOU G, WANG G, et al. Ensemble of software defect predictors: an AHP-based evaluation method [J]. International Journal of Information Technology and Decision Making, 2011, 10(1): 187-206. [7] ZHENG J. Cost-sensitive boosting neural networks for software defect prediction [J]. Expert Systems with Applications, 2010, 37(6): 4537-4543. [8] GRAY D, BOWES D, DAVEY N, et al. Reflections on the NASA MDP data sets [J]. IET Software, 2012, 6(6): 549-558. [9] 姜慧研,宗茂,刘相莹.基于ACO-SVM的软件缺陷预测模型的研究[J].计算机学报,2011,34(6):1148-1154.(JIANG H Y, ZONG M, LIU X Y. Research of software defect prediction model based on ACO-SVM [J]. Chinese Journal of Computers, 2011, 34(6): 1148-1154.) [10] ELISH K O, ELISH M O. Predicting defect-prone software modules using support vector machines [J]. Journal of Systems and Software, 2008, 81(5): 649-660. [11] KHOSHGOFTAAR T M, SELIYA N. Software quality classification modeling using the SPRINT decision tree algorithm [C]// ICTAI '02: Proceedings of the 14th IEEE International Conference on Tools with Artificial Intelligence. Washington, DC: IEEE Computer Society, 2002: 365-374. [12] ARAR Ö F, AYAN K. Software defect prediction using cost-sensitive neural network [J]. Applied Soft Computing, 2015, 33(C): 263-277. [13] ABDI H, WILLIAMS L J. Principal component analysis [J]. Wiley Interdisciplinary Reviews: Computational Statistics, 2010, 2(4): 433-459. [14] VIDAL R, MA Y, SASTRY S. Generalized Principal Component Analysis (GPCA) [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2005, 27(12): 1945-1959. [15] SELIYA N, KHOSHGOFTAAR T M. Software quality analysis of unlabeled program modules with semisupervised clustering [J]. IEEE Transactions on Systems, Man and Cybernetics, Part A: Systems and Humans, 2007, 37(2): 201-211. [16] BISHNU P S, BHATTACHERJEE V. Software fault prediction using quad tree-based K-means clustering algorithm [J]. IEEE Transactions on Knowledge and Data Engineering, 2012, 24(6): 1146-1150. [17] MA Y, ZHU S, QIN K, et al. Combining the requirement information for software defect estimation in design time [J]. Information Processing Letters, 2014, 114(9): 469-474. [18] GAO K, KHOSHGOFTAAR T M, WANG H, et al. Choosing software metrics for defect prediction: an investigation on feature selection techniques [J]. Software—Practice and Experience, 2011, 41(5): 579-606. [19] SMITH L N, ELAD M. Improving dictionary learning: multiple dictionary updates and coefficient reuse [J]. IEEE Signal Processing Letters, 2013, 20(1): 79-82. [20] YAN R, SHAO L, LIU Y. Nonlocal hierarchical dictionary learning using wavelets for image denoising [J]. IEEE Transactions on Image Processing, 2013, 22(12): 4689-4698. [21] MAIRAL J, ELAD M, SAPIRO G. Sparse representation for color image restoration [J]. IEEE Transactions on Image Processing, 2008, 17(1): 53-69. [22] MARCHESINI S. Invited article: a unified evaluation of iterative projection algorithms for phase retrieval [J]. Review of Scientific Instruments, 2007, 78(1): 011301. [23] LUISIER F, BLU T, UNSER M. A new SURE approach to image denoising: interscale orthonormal wavelet thresholding [J]. IEEE Transactions on Image Processing, 2007, 16(3): 593-606. [24] YANG M, ZHANG L, YANG J, et al. Metaface learning for sparse representation based face recognition [EB/OL]. [2015-11-26]. http://www4.comp.polyu.edu.hk/~cslzhang/paper/conf/ICIP2010/ICIP10_3551_YM.pdf. [25] JING X-Y, YING S, ZHANG Z-W, et al. Dictionary learning based software defect prediction [C]// ICSE 2014: Proceedings of the 36th International Conference on Software Engineer. New York: ACM, 2014: 414-423. |