4 papers
A Single Patch Is Not Enough: Deterministic Fusion of Repair Candidates
Boyang Yang, Xiangliang Hu, Luyao Ren +4
Modern LLM coding agents are commonly evaluated using pass@k, but developers typically apply a single final patch in real-world settings. This pass@k-to-pass@1 gap is a post-genera…
Input Reduction Enhanced LLM-based Program Repair
Boyang Yang, Luyao Ren, Xin Yin +3
Large Language Models (LLMs) have shown great potential in Automated Program Repair (APR). Test inputs, being crucial for reasoning the root cause of failures, are always included…
Effective Random Test Generation for Deep Learning Compilers
Luyao Ren, ZiHeng Wang, Yingfei Xiong +3
Deep learning compilers help address the difficulties of deploying deep learning models on diverse types of hardware. Testing deep learning compilers is highly crucial, because the…
Validity-Preserving Delta Debugging via Generator Trace Reduction
Luyao Ren, Xing Zhang, Ziyue Hua +4
Reducing test inputs that trigger bugs is crucial for efficient debugging. Delta debugging is the most popular approach for this purpose. When test inputs need to conform to certai…