---
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
        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
    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}
}
```