dataset_info:
- config_name: default
features:
- name: hash
dtype: string
- name: repo
dtype: string
- name: date
dtype: string
- name: license
dtype: string
- name: message
dtype: string
- name: mods
list:
- name: change_type
dtype: string
- name: old_path
dtype: string
- name: new_path
dtype: string
- name: diff
dtype: string
splits:
- name: test
num_examples: 163
- config_name: labels
features:
- name: hash
dtype: string
- name: repo
dtype: string
- name: date
dtype: string
- name: license
dtype: string
- name: message
dtype: string
- name: label
dtype: int8
- name: comment
dtype: string
splits:
- name: test
num_bytes: 272359
num_examples: 858
- config_name: retrieval_bm25
features:
- name: hash
dtype: string
- name: repo
dtype: string
- name: mods
dtype: string
- name: context
list:
- name: source
dtype: string
- name: content
dtype: string
configs:
- config_name: default
data_files:
- split: test
path: commitchronicle-py-long/test-*
- config_name: labels
data_files:
- split: test
path: commitchronicle-py-long-labels/test-*
- config_name: full_files
data_files:
- split: 4k
path: context/files/files_4k.parquet
- split: 8k
path: context/files/files_8k.parquet
- split: 16k
path: context/files/files_16k.parquet
- split: 32k
path: context/files/files_32k.parquet
- split: 64k
path: context/files/files_64k.parquet
- split: full
path: context/files/files_full.parquet
- config_name: retrieval_bm25
data_files:
- split: 4k
path: context/retrieval/bm25_4k.parquet
- split: 8k
path: context/retrieval/bm25_8k.parquet
- split: 16k
path: context/retrieval/bm25_16k.parquet
- split: 32k
path: context/retrieval/bm25_32k.parquet
- split: 64k
path: context/retrieval/bm25_64k.parquet
license: apache-2.0
ποΈ Long Code Arena (Commit message generation)
This is the benchmark for the Commit message generation task as part of the ποΈ Long Code Arena benchmark.
The dataset is a manually curated subset of the Python test set from the π€ CommitChronicle dataset, tailored for larger commits.
All the repositories are published under permissive licenses (MIT, Apache-2.0, and BSD-3-Clause). The datapoints can be removed upon request.
How-to
from datasets import load_dataset
dataset = load_dataset("JetBrains-Research/lca-cmg", split="test")
Note that all the data we have is considered to be in the test split.
Note. Working with git repositories
under repos
directory is not supported
via π€ Datasets. See Git Repositories section for more details.
About
Overview
In total, there are 163 commits from 34 repositories. For length statistics, refer to the notebook in our repository.
Dataset Structure
The dataset contains two kinds of data: data about each commit (under commitchronicle-py-long
folder) and compressed git repositories (under repos
folder).
Commits
Each example has the following fields:
Field | Description |
---|---|
repo |
Commit repository. |
hash |
Commit hash. |
date |
Commit date. |
license |
Commit repository's license. |
message |
Commit message. |
mods |
List of file modifications from a commit. |
Each file modification has the following fields:
Field | Description |
---|---|
change_type |
Type of change to current file. One of: ADD , COPY , RENAME , DELETE , MODIFY or UNKNOWN . |
old_path |
Path to file before change (might be empty). |
new_path |
Path to file after change (might be empty). |
diff |
git diff for current file. |
Data point example:
{'hash': 'b76ed0db81b3123ede5dc5e5f1bddf36336f3722',
'repo': 'apache/libcloud',
'date': '05.03.2022 17:52:34',
'license': 'Apache License 2.0',
'message': 'Add tests which verify that all OpenStack driver can be instantiated\nwith all the supported auth versions.\nNOTE: Those tests will fail right now due to the regressions being\nintroduced recently which breaks auth for some versions.',
'mods': [{'change_type': 'MODIFY',
'new_path': 'libcloud/test/compute/test_openstack.py',
'old_path': 'libcloud/test/compute/test_openstack.py',
'diff': '@@ -39,6 +39,7 @@ from libcloud.utils.py3 import u\n<...>'}],
}
Git Repositories
The compressed Git repositories for all the commits in this benchmark are stored under repos
directory.
Working with git repositories under repos
directory is not supported directly via π€ Datasets.
You can use huggingface_hub
package to download the repositories. The sample code is provided below:
import tarfile
from huggingface_hub import list_repo_tree, hf_hub_download
data_dir = "..." # replace with a path to where you want to store repositories locally
for repo_file in list_repo_tree("JetBrains-Research/lca-commit-message-generation", "repos", repo_type="dataset"):
file_path = hf_hub_download(
repo_id="JetBrains-Research/lca-commit-message-generation",
filename=repo_file.path,
repo_type="dataset",
local_dir=data_dir,
)
with tarfile.open(file_path, "r:gz") as tar:
tar.extractall(path=os.path.join(data_dir, "extracted_repos"))
For convenience, we also provide a full list of files in paths.json
.
After you download and extract the repositories, you can work with each repository either via Git or via Python libraries like GitPython or PyDriller.
Extra: longer context
Full Files
To facilitate further research, we additionally provide full contents of modified files before and after each commit in full_files
dataset config. full
split provides the whole files, and the remaining splits truncates each file
given the maximum allowed number of tokens n. The files are truncated uniformly, essentially, limiting the number of tokens for each file to max_num_tokens // num_files.
We use DeepSeek-V3 tokenizer to obtain the number of tokens.
from datasets import load_dataset
dataset = load_dataset("JetBrains-Research/lca-commit-message-generation",
"full_files",
split="16k" # should be one of: '4k', '8k', '16k', '32k', '64k', 'full'
)
Each example has the following fields:
repo
: commit repositoryhash
: commit hashmods
: commit modification (combined into a single diff)files
: a list of dictionaries, where each corresponds to a specific file changed in the commit and has the following keys:old_path
: file path before the commitold_contents
: file contents before the commitnew_path
: file path after the commitold_contents
: file contents after the commit
Retrieval
To facilitate further research, we additionally provide context for each commit as retrieved by BM25 retriever in retrieval_bm25
dataset config. For each commit, we run BM25 over all .py
files in the corresponding repository
at the state before the commit (excluding the files that were changed in this commit). We retrieve up to 50 files most relevant to the commit diff, and then, given the maximum allowed number of tokens n, we add files until the total context length (including diff)
in tokens returned by the DeepSeek-V3 tokenizer exceeds n, possibly trunctating the last included file.
To access these, run the following:
from datasets import load_dataset
dataset = load_dataset("JetBrains-Research/lca-commit-message-generation",
"retrieval_bm25",
split="16k" # should be one of: '4k', '8k', '16k', '32k', '64k'
)
Each example has the following fields:
repo
: commit repositoryhash
: commit hashmods
: commit modification (combined into a single diff)context
: context retrieved for the current commit; a list of dictionaries, where each corresponds to a specific file and has the following keys:source
: file pathcontent
: file content
π·οΈ Extra: commit labels
To facilitate further research, we additionally provide the manual labels for all the 858 commits that made it through initial filtering. The final version of the dataset described above consists of commits labeled either 4 or 5.
How-to
from datasets import load_dataset
dataset = load_dataset("JetBrains-Research/lca-commit-message-generation", "labels", split="test")
Note that all the data we have is considered to be in the test split.
About
Dataset Structure
Each example has the following fields:
Field | Description |
---|---|
repo |
Commit repository. |
hash |
Commit hash. |
date |
Commit date. |
license |
Commit repository's license. |
message |
Commit message. |
label |
Label of the current commit as a target for CMG task. |
comment |
Comment for a label for the current commit (optional, might be empty). |
Labels are in 1β5 scale, where:
- 1 β strong no
- 2 β weak no
- 3 β unsure
- 4 β weak yes
- 5 β strong yes
Data point example:
{'hash': '1559a4c686ddc2947fc3606e1c4279062cc9480f',
'repo': 'appscale/gts',
'date': '15.07.2018 21:00:39',
'license': 'Apache License 2.0',
'message': 'Add auto_id_policy and logs_path flags\n\nThese changes were introduced in the 1.7.5 SDK.',
'label': 1,
'comment': 'no way to know the version'}
Citing
@article{bogomolov2024long,
title={Long Code Arena: a Set of Benchmarks for Long-Context Code Models},
author={Bogomolov, Egor and Eliseeva, Aleksandra and Galimzyanov, Timur and Glukhov, Evgeniy and Shapkin, Anton and Tigina, Maria and Golubev, Yaroslav and Kovrigin, Alexander and van Deursen, Arie and Izadi, Maliheh and Bryksin, Timofey},
journal={arXiv preprint arXiv:2406.11612},
year={2024}
}
You can find the paper here.