Improving actionable warning identification via the refined warning-inducing context representation

• Published in: Science China. Information sciences Vol. 67; no. 5; p. 159101
• Main Authors: Ge, Xiuting, Fang, Chunrong, Li, Xuanye, Zhang, Quanjun, Liu, Jia, Zhao, Zhihong, Chen, Zhenyu
• Format: Journal Article
• Language: English
• Published: Beijing Science China Press 01-05-2024; Springer Nature B.V
• Subjects: Computer Science; Context; Information Systems and Communication Service; Letter; Representations; Warning
• ISSN: 1674-733X; 1869-1919
• DOI: 10.1007/s11432-023-3975-6

Conclusion
We improve AWI via the refined warning-inducing context representation, which captures both lexical and structural information for AWI from the refined warning-inducing context. We conduct experiments on over 51K+ warnings from 56 releases of five large-scale and open-source projects. The results in both within-project and cross-project AWI show that our approach is more effective than four state-of-the-art ML-based AWI approaches.