Analysis of 35k AI-referencing GitHub comments shows primary use for code implementation, with evolution toward conceptual support and sustained human refinement over time.
Empirical Softw
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
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cs.SE 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
Specificity and Context predict actionable code generation while Verification predicts adoption and Context predicts integration depth in LLM-assisted PR workflows.
citing papers explorer
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Empirical Study on the Characteristics and Evolution of AI-usage in GitHub Repositories: Evidence from Code Comments
Analysis of 35k AI-referencing GitHub comments shows primary use for code implementation, with evolution toward conceptual support and sustained human refinement over time.
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Prompt Quality and Pull Request Outcomes: A Stage-Based Empirical Study of LLM-Assisted Development
Specificity and Context predict actionable code generation while Verification predicts adoption and Context predicts integration depth in LLM-assisted PR workflows.