49 citations · 142 across the 10 of their papers we have counts for
10 papers
SimADFuzz: Simulation-Feedback Fuzz Testing for Autonomous Driving Systems
Huiwen Yang, Yu Zhou, Taolue Chen
Autonomous driving systems (ADS) have achieved remarkable progress in recent years. However, ensuring their safety and reliability remains a critical challenge due to the complexit…
Chain-of-Thought in Neural Code Generation: From and For Lightweight Language Models
Guang Yang, Yu Zhou, Xiang Chen +3
Large Language Models (LLMs) have demonstrated remarkable potential in code generation. The integration of Chain of Thought (CoT) reasoning can further boost their performance. How…
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…
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…
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…
DRIVE: Dockerfile Rule Mining and Violation Detection
Yu Zhou, Weilin Zhan, Zi Li +3
A Dockerfile defines a set of instructions to build Docker images, which can then be instantiated to support containerized applications. Recent studies have revealed a considerable…
How Important are Good Method Names in Neural Code Generation? A Model Robustness Perspective
Guang Yang, Yu Zhou, Wenhua Yang +3
Pre-trained code generation models (PCGMs) have been widely applied in neural code generation which can generate executable code from functional descriptions in natural languages,…
Adversarial Robustness of Deep Code Comment Generation
Yu Zhou, Xiaoqing Zhang, Juanjuan Shen +3
Deep neural networks (DNNs) have shown remarkable performance in a variety of domains such as computer vision, speech recognition, or natural language processing. Recently they als…
Boosting API Recommendation with Implicit Feedback
Yu Zhou, Xinying Yang, Taolue Chen +3
Developers often need to use appropriate APIs to program efficiently, but it is usually a difficult task to identify the exact one they need from a vast of candidates. To ease the…
User Review-Based Change File Localization for Mobile Applications
Yu Zhou, Yanqi Su, Taolue Chen +3
In the current mobile app development, novel and emerging DevOps practices (e.g., Continuous Delivery, Integration, and user feedback analysis) and tools are becoming more widespre…