collaborators

7 papers

cs.SE2026

Effective and Efficient Context Retrieval via Partial Dependency Graph for Repository-Level Code Generation

Zhongxin Liu, Zhonghao Jiang, Zhifan Ye +3

LLM-based repository-level code generation aims to generate code using the context available in a software repository, requiring LLMs to reason over complex code dependencies. Due…

cs.SE2026

DISTINCT: A Description-Guided Branch-Consistency Analysis Framework for Non-Regressive Test Case Generation

Pengyu Xue, Yuxiang Zhang, Zhen Yang +5

Automated test-generation research overwhelmingly assumes the correctness of focal methods, yet practitioners routinely face non-regression scenarios where the focal method may be…

cs.SE2025

Issue Localization via LLM-Driven Iterative Code Graph Searching

Zhonghao Jiang, Xiaoxue Ren, Meng Yan +3

Issue solving aims to generate patches to fix reported issues in real-world code repositories according to issue descriptions. Issue localization forms the basis for accurate issue…

cs.CV2025

Runtime Failure Hunting for Physics Engine Based Software Systems: How Far Can We Go?

Shuqing Li, Qiang Chen, Xiaoxue Ren +1

Physics Engines (PEs) are fundamental software frameworks that simulate physical interactions in applications ranging from entertainment to safety-critical systems. Despite their i…

cs.SE2025

AdaCoder: An Adaptive Planning and Multi-Agent Framework for Function-Level Code Generation

Yueheng Zhu, Chao Liu, Xuan He +4

Recently, researchers have proposed many multi-agent frameworks for function-level code generation, which aim to improve software development productivity by automatically generati…

cs.SE2025

FlexFL: Flexible and Effective Fault Localization with Open-Source Large Language Models

Chuyang Xu, Zhongxin Liu, Xiaoxue Ren +3

Due to the impressive code comprehension ability of Large Language Models (LLMs), a few studies have proposed to leverage LLMs to locate bugs, i.e., LLM-based FL, and demonstrated…