5 papers · 1 filter
SWE-Test: Benchmarking LLM Vulnerability Discovery via Input Prediction
Yuanxiang Shi, Jiayi Lin, Xuanyong Lin +8
Vulnerability discovery is becoming an important ability of large language model (LLM) agents: agents that silently miss real defects leave critical software exposed. Rigorously me…
MOA: A Profiling-Guided LLM Framework for Memory-Optimization Automation at Codebase Scale
Jiaxi Liang, Yuanxiang Shi, Zezhou Yang +1
Modern large-scale software systems often suffer from pervasive memory inefficiencies (e.g., bloat, churn), leading to excessive resource costs and performance degradation. Existin…
CodeFuse-CommitEval: Towards Benchmarking LLM's Power on Commit Message and Code Change Inconsistency Detection
Qingyu Zhang, Puzhuo Liu, Peng Di +1
Version control relies on commit messages to convey the rationale for code changes, but these messages are often low quality and, more critically, inconsistent with their diffs-kno…
CONGRA: Benchmarking Automatic Conflict Resolution
Qingyu Zhang, Liangcai Su, Kai Ye +1
Resolving conflicts from merging different software versions is a challenging task. To reduce the overhead of manual merging, researchers develop various program analysis-based too…
WizardMerge -- Save Us From Merging Without Any Clues
Qingyu Zhang, Junzhe Li, Jiayi Lin +3
Modern software development necessitates efficient version-oriented collaboration among developers. While Git is the most popular version control system, it generates unsatisfactor…