3 citations · 3 across the 13 of their papers we have counts for
7 papers · 1 filter
Route-Align-Verify for Functional Correctness in Code Generation
Erxue Zhou, Jingxiang Meng, Aofan Liu
Large language models (LLMs) have substantially improved code generation, yet achieving strong functional correctness remains difficult, especially for heterogeneous programming ta…
TestExplora: Benchmarking LLMs for Proactive Bug Discovery via Repository-Level Test Generation
Steven Liu, Jane Luo, Xin Zhang +7
Given that Large Language Models (LLMs) are increasingly applied to automate software development, comprehensive software assurance spans three distinct goals: regression preventio…
GraphLocator: Graph-guided Causal Reasoning for Issue Localization
Wei Liu, Chao Peng, Pengfei Gao +4
The issue localization task aims to identify the locations in a software repository that requires modification given a natural language issue description. This task is fundamental…
Attention Distance: A Novel Metric for Directed Fuzzing with Large Language Models
Wang Bin, Ao Yang, Kedan Li +5
In the domain of software security testing, Directed Grey-Box Fuzzing (DGF) has garnered widespread attention for its efficient target localization and excellent detection performa…
RefleXGen:The unexamined code is not worth using
Bin Wang, Hui Li, AoFan Liu +7
Security in code generation remains a pivotal challenge when applying large language models (LLMs). This paper introduces RefleXGen, an innovative method that significantly enhance…
Beyond Function-Level Search: Repository-Aware Dual-Encoder Code Retrieval with Adversarial Verification
Aofan Liu, Shiyuan Song, Haoxuan Li +2
The escalating complexity of modern codebases has intensified the need for retrieval systems capable of interpreting cross-component change intents, a capability fundamentally abse…
RA-Gen: A Controllable Code Generation Framework Using ReAct for Multi-Agent Task Execution
Aofan Liu, Haoxuan Li, Bin Wang +2
Code generation models based on large language models (LLMs) have gained wide adoption, but challenges remain in ensuring safety, accuracy, and controllability, especially for comp…