LintEval: Benchmarking LLMs on Linter-Guided File Refactoring
Linters are widely used in code maintenance and real-time IDE editing to surface lint alerts related to performance, style, error-prone, and other patterns in source files. However, existing code benchmarks do not explicitly evaluate linter-guided file refactoring, where models must reduce lint alerts in source files with correct initial functionality while satisfying functionality preservation. We introduce LintEval, a multilingual benchmark for linter-guided file refactoring across C++, Python, and Java, comprising 13,061 programs with correct initial functionality and 171,662 lint alerts extracted using language-specific linters. LintEval jointly evaluates functionality preservation, l...
| Authors | Tongwei Deng, Jinyu Zhu, Yue Cao et al. |
|---|---|
| Primary category | cs.SE |
| Published | 14 October 2026 |
| Last updated at source | 14 October 2026 |
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