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20202026
most citedComparison of Static Application Security Testing Tools and Large Language Models for Repo-level Vulnerability Detection

4 citations · 11 across the 13 of their papers we have counts for

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10 papers · 1 filter

cs.SE2026

Athena: Vulnerability-Affected Library Identification via Knowledge Graph Completion

Phong Trinh Duy, Trang Dang Yen, Hung Nguyen-Huu +5

A single vulnerability in a widely used library can cascade through millions of dependent applications, yet more than half of vulnerability database entries contain missing or inco…

cs.SE2026

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…

cs.SE2025

Optimizing Spectral Signature in Code Backdoor Detection

Quoc Hung Le, Thanh Le-Cong, Bach Le +1

As Large Language Models (LLMs) are increasingly integrated into software development workflows, they also become prime targets for adversarial attacks. Among these, backdoor attac…

cs.SE2024

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…

cs.SE2024★ 4 cited

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…

cs.SE2024

LEGION: Harnessing Pre-trained Language Models for GitHub Topic Recommendations with Distribution-Balance Loss

Yen-Trang Dang, Thanh-Le Cong, Phuc-Thanh Nguyen +4

Open-source development has revolutionized the software industry by promoting collaboration, transparency, and community-driven innovation. Today, a vast amount of various kinds of…

cs.SE2024★ 3 cited

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…

cs.SE2023★ 1 cited

Are We Ready to Embrace Generative AI for Software Q&A?

Bowen Xu, Thanh-Dat Nguyen, Thanh Le-Cong +8

Stack Overflow, the world's largest software Q&A (SQA) website, is facing a significant traffic drop due to the emergence of generative AI techniques. ChatGPT is banned by Stack Ov…

cs.SE2023★ 2 cited

PatchZero: Zero-Shot Automatic Patch Correctness Assessment

Xin Zhou, Bowen Xu, Kisub Kim +5

Automated Program Repair (APR) techniques have shown more and more promising results in fixing real-world bugs. Despite the effectiveness, APR techniques still face an overfitting…

cs.SE2020★ 1 cited

Adversarial Patch Generation for Automated Program Repair

Abdulaziz Alhefdhi, Hoa Khanh Dam, Thanh Le-Cong +2

Automated Program Repair has attracted significant research in recent years, leading to diverse techniques that focus on two main directions: search-based and semantic-based progra…