Open access
Aug 2026
Applying Cost-Sensitive Learning to Mitigate the Effect of Class Imbalance for Deep Learning-based Fault Localization
This work proposes applying cost-sensitive learning to set different weights for each sample to optimize the performance of fault localization and demonstrates that applying cost-sensitive learning can effectively alleviate the class imbalance problem in DLFL.
Yue Yan, Shu-Juan Jiang, Yanmei Zhang et al.
· International journal of sof... · 0 citations