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20242026
most citedEvaluating Large Language Models for Line-Level Vulnerability Localization

3 citations · 4 across the 2 of their papers we have counts for

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11 papers · 1 filter

cs.SE20261 cited

Software Development Life Cycle Perspective: A Survey of Benchmarks for Code Large Language Models and Agents

Kaixin Wang, Tianlin Li, Xiaoyu Zhang +7

Code large language models (CodeLLMs) and agents are increasingly being integrated into complex software engineering tasks spanning the entire Software Development Life Cycle (SDLC…

cs.SE20253 cited

Evaluating Large Language Models for Line-Level Vulnerability Localization

Jian Zhang, Chong Wang, Anran Li +4

Recently, Automated Vulnerability Localization (AVL) has attracted growing attention, aiming to facilitate diagnosis by pinpointing the specific lines of code responsible for vulne…

cs.SE2025

VFArchē: A Dual-Mode Framework for Locating Vulnerable Functions in Open-Source Software

Lyuye Zhang, Jian Zhang, Kaixuan Li +6

Software Composition Analysis (SCA) has become pivotal in addressing vulnerabilities inherent in software project dependencies. In particular, reachability analysis is increasingly…

cs.SE2025

Fixing Outside the Box: Uncovering Tactics for Open-Source Security Issue Management

Lyuye Zhang, Jiahui Wu, Chengwei Liu +5

In the rapidly evolving landscape of software development, addressing security vulnerabilities in open-source software (OSS) has become critically important. However, existing rese…

cs.SE2025

Show Me Your Code! Kill Code Poisoning: A Lightweight Method Based on Code Naturalness

Weisong Sun, Yuchen Chen, Mengzhe Yuan +6

Neural code models (NCMs) have demonstrated extraordinary capabilities in code intelligence tasks. Meanwhile, the security of NCMs and NCMs-based systems has garnered increasing at…

cs.SE2025

LLMs Meet Library Evolution: Evaluating Deprecated API Usage in LLM-based Code Completion

Chong Wang, Kaifeng Huang, Jian Zhang +4

Large language models (LLMs), pre-trained or fine-tuned on large code corpora, have shown effectiveness in generating code completions. However, in LLM-based code completion, LLMs…