BoostAPR: Boosting Automated Program Repair via Execution-Grounded Reinforcement Learning with Dual Reward Models
BoostAPR is presented, a three-stage framework addressing challenges of supervised fine-tuning on execution-verified demonstrations with reasoning traces, training dual reward models from execution outcomes, and PPO optimization where the line-level model redistributes rewards to critical edit regions.