Empirical evaluation finds reasoning LLMs improve code correction across iterations using execution feedback and outperform non-reasoning models, with syntactic and runtime errors easier to fix than logical ones.
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cs.SE 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
TICoder improves repository-level code generation by 11.52% over prior methods through test-driven planning and implementation-aware code reuse on standard benchmarks.
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Unlocking LLM Code Correction with Iterative Feedback Loops
Empirical evaluation finds reasoning LLMs improve code correction across iterations using execution feedback and outperform non-reasoning models, with syntactic and runtime errors easier to fix than logical ones.
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TICoder: A Repository-Level Code Generation Framework with Test-Driven Planning and Implementation-Aware Reuse
TICoder improves repository-level code generation by 11.52% over prior methods through test-driven planning and implementation-aware code reuse on standard benchmarks.