4 papers
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…
KE: Matryoshka Unstructured Knowledge Editing of Large Language Models
Zian Su, Ziyang Huang, Kaiyuan Zhang +1
Large language models (LLMs) have emerged as powerful knowledge bases yet are limited by static training data, leading to issues such as hallucinations and safety risks. Editing a…
Source Code Foundation Models are Transferable Binary Analysis Knowledge Bases
Zian Su, Xiangzhe Xu, Ziyang Huang +2
Human-Oriented Binary Reverse Engineering (HOBRE) lies at the intersection of binary and source code, aiming to lift binary code to human-readable content relevant to source code,…
CodeArt: Better Code Models by Attention Regularization When Symbols Are Lacking
Zian Su, Xiangzhe Xu, Ziyang Huang +4
Transformer based code models have impressive performance in many software engineering tasks. However, their effectiveness degrades when symbols are missing or not informative. The…