AI coding agent adoption in OSS projects raises code complexity modestly but produces no causal reduction in newcomer participation per DiD estimates on matched GitHub projects.
Does the Initial Environment Impact the Future of Developers?,
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
years
2026 3verdicts
UNVERDICTED 3representative citing papers
Presents a dynamic partitioning parallel SMT framework with core-guided pruning and backbone detection that outperforms sequential Z3 and prior parallel solvers on SMT-COMP 2025 benchmarks across six logics.
This survey compiles the history, awards, funding, AI integrations, and open challenges of the ESBMC model checker from 2009 to 2026.
citing papers explorer
-
Decoupling Code Complexity from Newcomer Participation: A Causal Study of AI Coding Agent Adoption in OSS
AI coding agent adoption in OSS projects raises code complexity modestly but produces no causal reduction in newcomer participation per DiD estimates on matched GitHub projects.
-
ESBMC: A Survey of Its Evolution, Integration, and Future Directions in Formal Software Verification
This survey compiles the history, awards, funding, AI integrations, and open challenges of the ESBMC model checker from 2009 to 2026.