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Found 4 papers, 0 papers with code
Aligning LLMs for FL-free Program Repair
Our core insight is that LLM's APR capability can be greatly improved by simply aligning the output to their training objective and allowing them to refine the whole program without first performing fault localization.
EFFL: Egalitarian Fairness in Federated Learning for Mitigating Matthew Effect
Recent advances in federated learning (FL) enable collaborative training of machine learning (ML) models from large-scale and widely dispersed clients while protecting their privacy.
Efficient Pattern-based Static Analysis Approach via Regular-Expression Rules
Second, we evaluate Codegex in automated code review by running it on 4256 PRs where it generated 372 review comments and received 116 feedback.
The State and Future of Genetic Improvement
We report the discussion session at the sixth international Genetic Improvement workshop, GI-2019 @ ICSE, which was held as part of the 41st ACM/IEEE International Conference on Software Engineering on Tuesday 28th May 2019.
