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20232026
most citedComparison of Static Application Security Testing Tools and Large Language Models for Repo-level Vulnerability Detection

4 citations · 15 across the 14 of their papers we have counts for

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11 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

Vul4Py: Benchmarking Automated Vulnerability Repair in Python with Paired Exploit and Functional Oracles

Tan Bui, Ting Zhang, Ferdian Thung +4

Automated Vulnerability Repair (AVR) has advanced rapidly across program analysis, machine learning, and Large Language Models (LLMs), but a verifiable, head-to-head comparison of…

cs.SE2025

Semantics-Aligned, Curriculum-Driven, and Reasoning-Enhanced Vulnerability Repair Framework

Chengran Yang, Ting Zhang, Jinfeng Jiang +9

Current learning-based Automated Vulnerability Repair (AVR) approaches, while promising, often fail to generalize effectively in real-world scenarios. Our diagnostic analysis revea…

cs.SE2025

PatchSeeker: Mapping NVD Records to their Vulnerability-fixing Commits with LLM Generated Commits and Embeddings

Huu Hung Nguyen, Anh Tuan Nguyen, Thanh Le-Cong +8

Software vulnerabilities pose serious risks to modern software ecosystems. While the National Vulnerability Database (NVD) is the authoritative source for cataloging these vulnerab…

cs.SE2025

Fixseeker: An Empirical Driven Graph-based Approach for Detecting Silent Vulnerability Fixes in Open Source Software

Yiran Cheng, Ting Zhang, Lwin Khin Shar +6

Open source software vulnerabilities pose significant security risks to downstream applications. While vulnerability databases provide valuable information for mitigation, many sec…

cs.SE2024★ 2 cited

CleanVul: Automatic Function-Level Vulnerability Detection in Code Commits Using LLM Heuristics

Yikun Li, Ting Zhang, Ratnadira Widyasari +13

Accurate identification of software vulnerabilities is crucial for system integrity. Vulnerability datasets, often derived from the National Vulnerability Database (NVD) or directl…

cs.SE2024★ 2 cited

VERCATION: Precise Vulnerable Open-source Software Version Identification based on Static Analysis and LLM

Yiran Cheng, Ting Zhang, Lwin Khin Shar +6

Open-source software (OSS) has experienced a surge in popularity, attributed to its collaborative development model and cost-effective nature. However, the adoption of specific sof…

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★ 4 cited

Large Language Model for Vulnerability Detection: Emerging Results and Future Directions

Xin Zhou, Ting Zhang, David Lo

Previous learning-based vulnerability detection methods relied on either medium-sized pre-trained models or smaller neural networks from scratch. Recent advancements in Large Pre-T…

cs.SE2024★ 1 cited

Multi-LLM Collaboration + Data-Centric Innovation = 2x Better Vulnerability Repair

Xin Zhou, Kisub Kim, Bowen Xu +2

The advances of deep learning (DL) have paved the way for automatic software vulnerability repair approaches, which effectively learn the mapping from the vulnerable code to the fi…

cs.SE2023★ 2 cited

Explaining Explanation: An Empirical Study on Explanation in Code Reviews

Ratnadira Widyasari, Ting Zhang, Abir Bouraffa +2

Code reviews are central for software quality assurance. Ideally, reviewers should explain their feedback to enable authors of code changes to understand the feedback and act accor…