49 citations · 103 across the 9 of their papers we have counts for
Showing 2023Show all
3 papers · 1 filter
cs.SE2023★ 1 cited
Assessing and Improving Syntactic Adversarial Robustness of Pre-trained Models for Code Translation
Guang Yang, Yu Zhou, Xiangyu Zhang +3
Context: Pre-trained models (PTMs) have demonstrated significant potential in automatic code translation. However, the vulnerability of these models in translation tasks, particula…
cs.SE2023
A Syntax-Guided Multi-Task Learning Approach for Turducken-Style Code Generation
Guang Yang, Yu Zhou, Xiang Chen +4
Due to the development of pre-trained language models, automated code generation techniques have shown great promise in recent years. However, the generated code is difficult to me…
cs.SE2023
Test Reuse Based on Adaptive Semantic Matching across Android Mobile Applications
Shuqi Liu, Yu Zhou, Tingting Han +1
Automatic test generation can help verify and develop the behavior of mobile applications. Test reuse based on semantic similarities between applications of the same category has b…