12 papers
Three Heads Are Better Than One: A Multi-perspective Reasoning Framework for Enhanced Vulnerability Detection
Xin Peng, Bo Lin, Jing Wang +5
Automated vulnerability detection is crucial for enhancing software security by identifying potential flaws that attackers could exploit, thereby reducing the reliance on labor-int…
Atomizer: An LLM-based Collaborative Multi-Agent Framework for Intent-Driven Commit Untangling
Kangchen Zhu, Zhiliang Tian, Shangwen Wang +2
Composite commits, which entangle multiple unrelated concerns, are prevalent in software development and significantly hinder program comprehension and maintenance. Existing automa…
Exploring the Security Threats of Retriever Backdoors in Retrieval-Augmented Code Generation
Tian Li, Bo Lin, Shangwen Wang +1
Retrieval-Augmented Code Generation (RACG) is increasingly adopted to enhance Large Language Models for software development, yet its security implications remain dangerously under…
Give LLMs a Security Course: Securing Retrieval-Augmented Code Generation via Knowledge Injection
Bo Lin, Shangwen Wang, Yihao Qin +2
Retrieval-Augmented Code Generation (RACG) leverages external knowledge to enhance Large Language Models (LLMs) in code synthesis, improving the functional correctness of the gener…
Smoke and Mirrors: Jailbreaking LLM-based Code Generation via Implicit Malicious Prompts
Sheng Ouyang, Yihao Qin, Bo Lin +3
The proliferation of Large Language Models (LLMs) has revolutionized natural language processing and significantly impacted code generation tasks, enhancing software development ef…
Large Language Models-Aided Program Debloating
Bo Lin, Shangwen Wang, Yihao Qin +2
As software grows in complexity to accommodate diverse features and platforms, software bloating has emerged as a significant challenge, adversely affecting performance and securit…