5 papers · 1 filter
PatchGuru: Patch Oracle Inference from Natural Language Artifacts
Thanh Le-Cong, Bach Le, Toby Murray +2
As software systems evolve, patches may unintentionally alter program behavior. Validating patches against their intended semantics is difficult due to incomplete regression tests…
Memory-Efficient Large Language Models for Program Repair with Semantic-Guided Patch Generation
Thanh Le-Cong, Bach Le, Toby Murray
In this paper, we first show that increases in beam size, even for small-sized LLMs (1B-7B params), require extensive GPU usage, leading to up to 80% of recurring crashes due to me…
Signature in Code Backdoor Detection, how far are we?
Quoc Hung Le, Thanh Le-Cong, Bach Le +1
As Large Language Models (LLMs) become increasingly integrated into software development workflows, they also become prime targets for adversarial attacks. Among these, backdoor at…
Towards Reliable Evaluation of Neural Program Repair with Natural Robustness Testing
Thanh Le-Cong, Dat Nguyen, Bach Le +1
In this paper, we propose shifting the focus of robustness evaluation for Neural Program Repair (NPR) techniques toward naturally-occurring data transformations. To accomplish this…
Comparison of Static Application Security Testing Tools and Large Language Models for Repo-level Vulnerability Detection
Xin Zhou, Duc-Manh Tran, Thanh Le-Cong +5
Software vulnerabilities pose significant security challenges and potential risks to society, necessitating extensive efforts in automated vulnerability detection. There are two po…