PerfAgent: Profiler-Guided Iterative Refinement for Repository-Level Code Optimization
Large language model (LLM) agents now perform well on correctness-oriented repository-level tasks, including SWE-Bench issue resolution and feature implementation in real codebases. However, they still struggle with repository-level code optimization, which requires preserving behavior while improving runtime performance. Passing tests is not enough in this setting; a patch must preserve behavior, implement code optimization, and approach expert speedups. Current agents often miss bottlenecks hidden behind abstraction layers and native extensions, stop after shallow speedups, or insufficiently test the code patches that thus may silently break edge cases. We present PerfAgent, a profiler-...
| Authors | Ryan Deng, Yuanzhe Liu, Bastian Lipka et al. |
|---|---|
| Primary category | cs.SE |
| Published | 22 July 2026 |
| Last updated at source | 22 July 2026 |
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