1 citations · 2 across the 6 of their papers we have counts for
3 papers · 1 filter
Learning Program Semantics with Code Representations: An Empirical Study
Jing Kai Siow, Shangqing Liu, Xiaofei Xie +2
Program semantics learning is the core and fundamental for various code intelligent tasks e.g., vulnerability detection, clone detection. A considerable amount of existing works pr…
Devign: Effective Vulnerability Identification by Learning Comprehensive Program Semantics via Graph Neural Networks
Yaqin Zhou, Shangqing Liu, Jingkai Siow +2
Vulnerability identification is crucial to protect the software systems from attacks for cyber security. It is especially important to localize the vulnerable functions among the s…
METTLE: a METamorphic testing approach to assessing and validating unsupervised machine LEarning systems
Xiaoyuan Xie, Zhiyi Zhang, Tsong Yueh Chen +3
Unsupervised machine learning is the training of an artificial intelligence system using information that is neither classified nor labeled, with a view to modeling the underlying…