AI coding agent adoption causes no change in human contributor count but reduces contributor density and newcomer share by 3.7pp while increasing review depth by 5.3% in a staggered DiD analysis of 11k GitHub projects.
Early-stage prediction of review effort in ai-generated pull requests.CoRR, abs/2601.00753
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
citation-role summary
background 1
citation-polarity summary
fields
cs.SE 2years
2026 2verdicts
UNVERDICTED 2roles
background 1polarities
support 1representative citing papers
AI-generated code requires less maintenance than human-written code, mostly involving feature additions by humans rather than bug fixes.
citing papers explorer
-
Augmentation with Dilution: A Large-Scale Empirical Study of Human Contributor Ecosystems After AI Coding Agent Adoption
AI coding agent adoption causes no change in human contributor count but reduces contributor density and newcomer share by 3.7pp while increasing review depth by 5.3% in a staggered DiD analysis of 11k GitHub projects.
-
To What Extent Does Agent-generated Code Require Maintenance? An Empirical Study
AI-generated code requires less maintenance than human-written code, mostly involving feature additions by humans rather than bug fixes.