metadata

configs:
  - config_name: python
    data_files:
      - split: test
        path: data/python/*.json

🏟️ Long Code Arena (CI Fixing)

🛠️ CI Fixing: given logs of a failed GitHub Actions workflow and the corresponding repository shapshot, fix the repository contents in order to make the workflow pass.

This is the benchmark for CI Fixing task as part of 🏟️ Long Code Arena benchmark.

To score your model on this dataset, you can use CI Fixing benchmark (https://github.com/JetBrains-Research/lca-baselines/tree/main/ci-fixing/ci-fixing-benchmark)

How-to

List all the available configs via datasets.get_dataset_config_names and choose an appropriate one.

Current configs: python

Load the data via load_dataset:

from datasets import load_dataset

dataset = load_dataset("JetBrains-Research/lca-ci-fixing", split="test")

Note that all the data we have is considered to be in the test split.

Dataset Structure

This dataset contains logs of the failed GitHub Action workflows for some commits followed by the commit that passes the workflow successfully.

Note that, unlike many other 🏟 Long Code Arena datasets, this dataset doesn't contain repositories.

Our CI Fixing benchmark (🚧 todo) clones the necessary repos to the user's local machine. The user should run their model to fix the failing CI workflows, and the benchmark will push commits to GitHub, returning the results of the workflow runs for all the datapoints.

Datapoint Schema

Each example has the following fields:

Field	Description
`contributor`	Username of the contributor that committed changes
`difficulty`	Difficulty of the problem (assessor-based)
`diff`	Contents of the diff between the failed and the successful commits
`head_branch`	Name of the original branch that the commit was pushed at
`id`	Unique ID of the datapoint
`language`	Main language of the repo
`logs`	List of dicts with keys `log` (logs of the failed job, particular step) and `step_name` (name of the failed step of the job)
`repo_name`	Name of the original repo (second part of the `owner/name` on GitHub)
`repo owner`	Owner of the original repo (first part of the `owner/name` on GitHub)
`sha_fail`	SHA of the failed commit
`sha_success`	SHA of the successful commit
`workflow`	Contents of the workflow file
`workflow_filename`	The name of the workflow file (without directories)
`workflow_name`	The name of the workflow
`workflow_path`	The full path to the workflow file
`changed_files`	List of files changed in diff
`commit_link`	URL to commit corresponding to failed job

Datapoint Example

{'contributor': 'Gallaecio',
 'diff': 'diff --git a/scrapy/crawler.py b/scrapy/crawler.py/n<...>',
 'difficulty': '1',
 'head_branch': 'component-getters',
 'id': 18,
 'language': 'Python',
 'logs': [{'log': '##[group]Run pip install -U tox\n<...>',
           'step_name': 'checks (3.12, pylint)/4_Run check.txt'}],
 'repo_name': 'scrapy',
 'repo_owner': 'scrapy',
 'sha_fail': '0f71221cf9875ed8ef3400e1008408e79b6691e6',
 'sha_success': 'c1ba9ccdf916b89d875628ba143dc5c9f6977430',
 'workflow': 'name: Checks\non: [push, pull_request]\n\n<...>',
 'workflow_filename': 'checks.yml',
 'workflow_name': 'Checks',
 'workflow_path': '.github/workflows/checks.yml',
 'changed_files': ["scrapy/crawler.py"],
 'commit_link': "https://github.com/scrapy/scrapy/tree/0f71221cf9875ed8ef3400e1008408e79b6691e6"}