| ---
|
| license: mit
|
| task_categories:
|
| - text-generation
|
| language:
|
| - en
|
| - code
|
| tags:
|
| - code-review
|
| - benchmark
|
| - code-generation
|
| - software-engineering
|
| size_categories:
|
| - 10K<n<100K
|
| configs:
|
| - config_name: code-editing
|
| data_files:
|
| - split: train
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| path: data/code-editing/train/*.parquet
|
| - split: test
|
| path: data/code-editing/test/*.parquet
|
| - split: validation
|
| path: data/code-editing/validation/*.parquet
|
| - config_name: comment-generation
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| data_files:
|
| - split: train
|
| path: data/comment-generation/train/*.parquet
|
| - split: test
|
| path: data/comment-generation/test/*.parquet
|
| - split: validation
|
| path: data/comment-generation/validation/*.parquet
|
| - config_name: default
|
| data_files:
|
| - split: train
|
| path: data/code-editing/train/*.parquet
|
| - split: test
|
| path: data/code-editing/test/*.parquet
|
| - split: validation
|
| path: data/code-editing/validation/*.parquet
|
| ---
|
|
|
| # CodeReview-Bench
|
|
|
| A benchmark for evaluating models on two code review tasks, curated from [ronantakizawa/github-codereview](https://huggingface.co/datasets/ronantakizawa/github-codereview).
|
|
|
| ## Tasks
|
|
|
| ### 1. Code Editing
|
|
|
| Given code and a reviewer comment, apply the requested change.
|
|
|
| - **Input**: `before_code`, `reviewer_comment`, `language`, `diff_context`
|
| - **Target**: `after_code`
|
|
|
| ```python
|
| from datasets import load_dataset
|
|
|
| ds = load_dataset("ronantakizawa/codereview-bench", "code-editing")
|
| example = ds["test"][0]
|
|
|
| prompt = f"""Apply the following review comment to the code.
|
|
|
| Review: {example['reviewer_comment']}
|
|
|
| Code:
|
| {example['before_code']}
|
|
|
| Updated code:"""
|
| ```
|
|
|
| ### 2. Comment Generation
|
|
|
| Given a code diff, generate the review comment a human reviewer would write.
|
|
|
| - **Input**: `before_code`, `after_code`, `diff_context`, `language`
|
| - **Target**: `reviewer_comment`
|
|
|
| ```python
|
| ds = load_dataset("ronantakizawa/codereview-bench", "comment-generation")
|
| example = ds["test"][0]
|
|
|
| prompt = f"""Review the following code change and provide feedback.
|
|
|
| Before:
|
| {example['before_code']}
|
|
|
| After:
|
| {example['after_code']}
|
|
|
| Review comment:"""
|
| ```
|
|
|
| ## Filtering Criteria
|
|
|
| This benchmark is a quality-filtered subset of the full dataset:
|
|
|
| | Filter | Threshold |
|
| |--------|-----------|
|
| | Positive examples only | `is_negative = False` |
|
| | Quality score | >= 0.5 |
|
| | Comment length | >= 50 characters |
|
| | Code context | >= 10 lines (before and after) |
|
| | Comment types | bug, security, performance, refactor, suggestion |
|
|
|
| Excluded: nitpick, style, question, and negative examples.
|
|
|
| ## Schema
|
|
|
| ### Code Editing
|
|
|
| | Column | Type | Role |
|
| |--------|------|------|
|
| | `before_code` | string | Input |
|
| | `reviewer_comment` | string | Input |
|
| | `language` | string | Input |
|
| | `diff_context` | string | Input |
|
| | `after_code` | string | Target |
|
| | `repo_name` | string | Metadata |
|
| | `file_path` | string | Metadata |
|
| | `comment_type` | string | Metadata |
|
| | `quality_score` | float | Metadata |
|
|
|
| ### Comment Generation
|
|
|
| | Column | Type | Role |
|
| |--------|------|------|
|
| | `before_code` | string | Input |
|
| | `after_code` | string | Input |
|
| | `diff_context` | string | Input |
|
| | `language` | string | Input |
|
| | `reviewer_comment` | string | Target |
|
| | `repo_name` | string | Metadata |
|
| | `file_path` | string | Metadata |
|
| | `comment_type` | string | Metadata |
|
| | `quality_score` | float | Metadata |
|
|
|
| ## Evaluation
|
|
|
| ### Code Editing
|
|
|
| - **CodeBLEU**: Measures structural and syntactic similarity of generated code
|
| - **Exact match**: Percentage of outputs matching the target exactly
|
| - **Edit similarity**: Normalized edit distance between generated and target code
|
|
|
| ### Comment Generation
|
|
|
| - **BERTScore**: Semantic similarity between generated and reference comments
|
| - **ROUGE-L**: Longest common subsequence overlap
|
| - **Human evaluation**: Recommended for final assessment — automated metrics correlate poorly with review quality
|
|
|
| ## Splits
|
|
|
| | Split | Description |
|
| |-------|-------------|
|
| | train | Training data (90%) |
|
| | test | Held-out evaluation (5%) |
|
| | validation | Development/tuning (5%) |
|
|
|
| Splits are repo-deterministic — no repo appears in multiple splits.
|
|
|
| ## Citation
|
|
|
| ```bibtex
|
| @dataset{takizawa2026codereviewbench,
|
| title={CodeReview-Bench: A Benchmark for Review-Driven Code Changes},
|
| author={Takizawa, Ronan},
|
| year={2026},
|
| publisher={Hugging Face},
|
| url={https://huggingface.co/datasets/ronantakizawa/codereview-bench}
|
| }
|
| ```
|
|
|
