Leveraging Reviewer Experience in Code Review Comment Generation

Leveraging Reviewer Experience in Code Review Comment Generation (Replication Package) This is the replication package for journal paper "Leveraging Reviewer Experience in Code Review Comment Generation". Authors Hong Yi Lin (University of Melbourne) Patanamon Thongtanunam (University of Melbourne) Christoph Treude (Singapore Management University) Michael Godfrey (University of Waterloo) Chunhua Liu (University of Melbourne) Wachiraphan Charoenwet (University of Melbourne) List of Contents Manual_Evaluation Accuracy annotations Informativeness annotations Comment category annotations Manual annotation guidelines 100 random samples ELF_AVG Model checkpoints for ELF_AVG strategy (Repository, Subsystem, Package) ELF_ACO Model checkpoints for ELF_ACO strategy (Repository, Subsystem, Package) ELF_MAX Model checkpoints for ELF_MAX strategy (Repository, Subsystem, Package) ELF_RSO Model checkpoints for ELF_RSO strategy (Repository, Subsystem, Package) Oversampling Model checkpoints for Experience-Aware Oversampling (Repository) CodeReviewer Model checkpoints for the original CodeReviewer (Fine-tuned on our dataset) Predictions All model generated predictions for test set Repository_History Pull request and commit histories for all repositories in training, validation and test set Code_Review_Dataset_Tagged Cleaned training, validation and test set including tagged ownership ratios Top10_B4_Delta Top 10 generations for each ELF model vs CodeReviewer in terms of BLEU-4 ELF_Code Fine-tuning and testing scripts for ELF (Adapted from CodeReviewer)