15 citations · 70 across the 10 of their papers we have counts for
10 papers
Intention is All You Need: Refining Your Code from Your Intention
Qi Guo, Xiaofei Xie, Shangqing Liu +3
Code refinement aims to enhance existing code by addressing issues, refactoring, and optimizing to improve quality and meet specific requirements. As software projects scale in siz…
Multi-label Classification for Android Malware Based on Active Learning
Qijing Qiao, Ruitao Feng, Sen Chen +2
The existing malware classification approaches (i.e., binary and family classification) can barely benefit subsequent analysis with their outputs. Even the family classification ap…
FT2Ra: A Fine-Tuning-Inspired Approach to Retrieval-Augmented Code Completion
Qi Guo, Xiaohong Li, Xiaofei Xie +6
The rise of code pre-trained models has significantly enhanced various coding tasks, such as code completion, and tools like GitHub Copilot. However, the substantial size of these…
EndWatch: A Practical Method for Detecting Non-Termination in Real-World Software
Yao Zhang, Xiaofei Xie, Yi Li +3
Detecting non-termination is crucial for ensuring program correctness and security, such as preventing denial-of-service attacks. While termination analysis has been studied for ma…
Exploring the Potential of ChatGPT in Automated Code Refinement: An Empirical Study
Qi Guo, Junming Cao, Xiaofei Xie +4
Code review is an essential activity for ensuring the quality and maintainability of software projects. However, it is a time-consuming and often error-prone task that can signific…
Automated and Context-Aware Repair of Color-Related Accessibility Issues for Android Apps
Yuxin Zhang, Sen Chen, Lingling Fan +2
Approximately 15% of the world's population is suffering from various disabilities or impairments. However, many mobile UX designers and developers disregard the significance of ac…
Towards Understanding the Faults of JavaScript-Based Deep Learning Systems
Lili Quan, Qianyu Guo, Xiaofei Xie +3
Quality assurance is of great importance for deep learning (DL) systems, especially when they are applied in safety-critical applications. While quality issues of native DL applica…
AVA: Adversarial Vignetting Attack against Visual Recognition
Binyu Tian, Felix Juefei-Xu, Qing Guo +3
Vignetting is an inherited imaging phenomenon within almost all optical systems, showing as a radial intensity darkening toward the corners of an image. Since it is a common effect…
Bias Field Poses a Threat to DNN-based X-Ray Recognition
Binyu Tian, Qing Guo, Felix Juefei-Xu +5
The chest X-ray plays a key role in screening and diagnosis of many lung diseases including the COVID-19. More recently, many works construct deep neural networks (DNNs) for chest…
An Orchestrated Empirical Study on Deep Learning Frameworks and Platforms
Qianyu Guo, Xiaofei Xie, Lei Ma +6
Deep learning (DL) has recently achieved tremendous success in a variety of cutting-edge applications, e.g., image recognition, speech and natural language processing, and autonomo…