首页|Reports Outline Machine Learning Study Results from Shanghai Jiao Tong Universit y (Code-aware Fault Localization With Pretraining and Interpretable Machine Lea rning)
Reports Outline Machine Learning Study Results from Shanghai Jiao Tong Universit y (Code-aware Fault Localization With Pretraining and Interpretable Machine Lea rning)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Current study results on Machine Learn ing have been published. According to news originating from Ningbo, People’s Rep ublic of China, by NewsRx correspondents, research stated, “Following the rapid development of deep learning, many studies in the field of fault localization (F L) have utilized deep learning to analyze statements’ coverage information (i.e. , executed or not executed) and test cases’ results (i.e., failing or passing), which have shown dramatic ability in identifying suspicious statements potential ly responsible for failures. However, they mainly pay attention to the binary in formation of executing test cases but ignore incorporating code snippets and the ir inner relationships into the learning process.”
NingboPeople’s Republic of ChinaAsiaCyborgsEmerging TechnologiesMachine LearningShanghai Jiao Tong University
NETL
NSTL
