16 citations · 45 across the 20 of their papers we have counts for
20 papers
Breaking Customized LLMs for Coding: Automated Red Teaming for Instruction Backdoor Attacks
Yuchen Chen, Wei Cheng, Yuan Xiao +5
LLM customization platforms allow users to build task-specific models for code intelligence tasks by embedding instructions into system prompts, without modifying the underlying mo…
Securing Code Understanding: Detecting Natural Backdoor Vulnerability in Code Language Models
Yuchen Chen, Weisong Sun, Haocheng Huang +11
Code Language Models (CodeLMs) have become integral to software engineering, significantly advancing code intelligence tasks. However, their widespread adoption has raised critical…
Execution-Grounded Security Testing for Coding Agents in Software Engineering Pipelines
Yifei Ge, Weisong Sun, Jinkun Xiao +8
Coding agents are increasingly integrated into system operations, where their tool use can directly modify project artifacts, execution environments, and the underlying system. For…
Probing Privacy Leaks in LLM-based Code Generation via Test Generation
Yifei Ge, Zhenpeng Chen, Weisong Sun +7
The widespread availability of large-scale code datasets has fueled the rapid development of large language models (LLMs) for code-related tasks. These datasets may include sensiti…
PuzzleMark: Implicit Jigsaw Learning for Robust Code Dataset Watermarking in Neural Code Completion Models
Haocheng Huang, Yuchen Chen, Weisong Sun +5
Constructing and curating high-quality code datasets requires significant resources, making them valuable intellectual property. Unfortunately, these datasets currently face severe…
Enhancing and Reporting Robustness Boundary of Neural Code Models for Intelligent Code Understanding
Tingxu Han, Wei Song, Weisong Sun +6
With the development of deep learning, Neural Code Models (NCMs) such as CodeBERT and CodeLlama are widely used for code understanding tasks, including defect detection and code cl…
Commenting Higher-level Code Unit: Full Code, Reduced Code, or Hierarchical Code Summarization
Weisong Sun, Yiran Zhang, Jie Zhu +8
Commenting code is a crucial activity in software development, as it aids in facilitating future maintenance and updates. To enhance the efficiency of writing comments and reduce d…
Show Me Your Code! Kill Code Poisoning: A Lightweight Method Based on Code Naturalness
Weisong Sun, Yuchen Chen, Mengzhe Yuan +6
Neural code models (NCMs) have demonstrated extraordinary capabilities in code intelligence tasks. Meanwhile, the security of NCMs and NCMs-based systems has garnered increasing at…
Demonstration Attack against In-Context Learning for Code Intelligence
Yifei Ge, Weisong Sun, Yihang Lou +7
Recent advancements in large language models (LLMs) have revolutionized code intelligence by improving programming productivity and alleviating challenges faced by software develop…
Security of Language Models for Code: A Systematic Literature Review
Yuchen Chen, Weisong Sun, Chunrong Fang +7
Language models for code (CodeLMs) have emerged as powerful tools for code-related tasks, outperforming traditional methods and standard machine learning approaches. However, these…
SoVAR: Building Generalizable Scenarios from Accident Reports for Autonomous Driving Testing
An Guo, Yuan Zhou, Haoxiang Tian +7
Autonomous driving systems (ADSs) have undergone remarkable development and are increasingly employed in safety-critical applications. However, recently reported data on fatal acci…
Eliminating Backdoors in Neural Code Models for Secure Code Understanding
Weisong Sun, Yuchen Chen, Chunrong Fang +7
Neural code models (NCMs) have been widely used to address various code understanding tasks, such as defect detection. However, numerous recent studies reveal that such models are…
Source Code Summarization in the Era of Large Language Models
Weisong Sun, Yun Miao, Yuekang Li +6
To support software developers in understanding and maintaining programs, various automatic (source) code summarization techniques have been proposed to generate a concise natural…
ESALE: Enhancing Code-Summary Alignment Learning for Source Code Summarization
Chunrong Fang, Weisong Sun, Yuchen Chen +7
(Source) code summarization aims to automatically generate succinct natural language summaries for given code snippets. Such summaries play a significant role in promoting develope…
Pre-trained Model-based Actionable Warning Identification: A Feasibility Study
Xiuting Ge, Chunrong Fang, Quanjun Zhang +8
Actionable Warning Identification (AWI) plays a pivotal role in improving the usability of static code analyzers. Currently, Machine Learning (ML)-based AWI approaches, which mainl…
Can Distillation Mitigate Backdoor Attacks in Pre-trained Encoders?
TIngxu Han, Wei Song, Weisong Sun +7
Self-Supervised Learning (SSL) has become a prominent paradigm for pre-training encoders to learning general-purpose representations from unlabeled data and releasing them on third…
A Prompt Learning Framework for Source Code Summarization
Tingting Xu, Yun Miao, Chunrong Fang +8
(Source) code summarization is the task of automatically generating natural language summaries (also called comments) for given code snippets. Recently, with the successful applica…
Abstract Syntax Tree for Programming Language Understanding and Representation: How Far Are We?
Weisong Sun, Chunrong Fang, Yun Miao +8
Programming language understanding and representation (a.k.a code representation learning) has always been a hot and challenging task in software engineering. It aims to apply deep…
Machine Learning for Actionable Warning Identification: A Comprehensive Survey
Xiuting Ge, Chunrong Fang, Xuanye Li +7
Actionable Warning Identification (AWI) plays a crucial role in improving the usability of static code analyzers. With recent advances in Machine Learning (ML), various approaches…
A Survey of Source Code Search: A 3-Dimensional Perspective
Weisong Sun, Chunrong Fang, Yifei Ge +6
(Source) code search is widely concerned by software engineering researchers because it can improve the productivity and quality of software development. Given a functionality requ…