4 papers
Human-Machine Co-Boosted Bug Report Identification with Mutualistic Neural Active Learning
Guoming Long, Shihai Wang, Hui Fang +1
Bug reports, encompassing a wide range of bug types, are crucial for maintaining software quality. However, the increasing complexity and volume of bug reports pose a significant c…
Learning Software Bug Reports: A Systematic Literature Review
Guoming Long, Jingzhi Gong, Hui Fang +1
The recent advancement of artificial intelligence, especially machine learning (ML), has significantly impacted software engineering research, including bug report analysis. ML aim…
Multifaceted Hierarchical Report Identification for Non-Functional Bugs in Deep Learning Frameworks
Guoming Long, Tao Chen, Georgina Cosma
Non-functional bugs (e.g., performance- or accuracy-related bugs) in Deep Learning (DL) frameworks can lead to some of the most devastating consequences. Reporting those bugs on a…
On Reporting Performance and Accuracy Bugs for Deep Learning Frameworks: An Exploratory Study from GitHub
Guoming Long, Tao Chen
The tremendous success of Deep Learning (DL) has significantly boosted the number of open-sourced DL frameworks hosted on GitHub. Among others, performance and accuracy bugs are cr…