4 papers
When Ambiguity Meets Atypicality: Dual-Perspective Test Input Prioritization for DNNs
Haoran Li, Shihai Wang, Bin Liu +5
While Deep Neural Networks (DNNs) have achieved remarkable progress in cutting-edge domains, their inherent brittleness has become a growing concern. To ensure the reliability and…
Conjecture and Inquiry: Quantifying Software Performance Requirements via Interactive Retrieval-Augmented Preference Elicitation
Shihai Wang, Tao Chen
Since software performance requirements are documented in natural language, quantifying them into mathematical forms is essential for software engineering. Yet, the vagueness in pe…
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…
Light over Heavy: Automated Performance Requirements Quantification with Linguistic Inducement
Shihai Wang, Tao Chen
Elicited performance requirements need to be quantified for compliance in different engineering tasks, e.g., configuration tuning and performance testing. Much existing work has re…