collaborators

17 papers

cs.SE2026

A Unified Issue Resolution Benchmark for Requirement Clarification, Planning, and Code Generation for Coding Agents

Xin Zhou, Chun Yong Chong, Kisub Kim +11

Large language model-powered coding agents are increasingly used to modify existing code repositories, for example, by adding features or fixing bugs. Yet existing repository-level…

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.SE2026

What Resolve Rate Hides: Trajectory Structure Diagnostics for Coding Agents

Rui Shu, Chun Yong Chong, Xin Zhou +6

Coding agents are ranked almost entirely by resolve rate: whether their final patch passes the target tests. Yet two agents can reach the same outcome through very different proces…

cs.SE2026

SecureVibeBench: Benchmarking Secure Vibe Coding of AI Agents via Reconstructing Vulnerability-Introducing Scenarios

Junkai Chen, Huihui Huang, Yunbo Lyu +10

Large language model-powered code agents are rapidly transforming software engineering, yet the security risks of their generated code have become a critical concern. Existing benc…

cs.SE2026

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.CR2026

Beyond Function-Level Analysis: Context-Aware Reasoning for Inter-Procedural Vulnerability Detection

Yikun Li, Ting Zhang, Jieke Shi +10

Recent progress in ML and LLMs has improved vulnerability detection, and recent datasets have reduced label noise and unrelated code changes. However, most existing approaches stil…