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bug-localization

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metadata
license: other
dataset_info:
  - config_name: java
    features:
      - name: id
        dtype: int64
      - name: text_id
        dtype: string
      - name: repo_owner
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        dtype: string
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        dtype: string
      - name: comment_url
        dtype: string
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      - name: link_keyword
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        dtype: int64
      - name: issue_links_count
        dtype: int64
      - name: issue_code_blocks_count
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      - name: pull_create_at
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      - name: stars
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      - name: language
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      - name: languages
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      - name: license
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      - name: pull_url
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      - name: links_count
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      - name: java_changed_files_count
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  - config_name: py
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      - name: head_sha
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        dtype: timestamp[s]
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configs:
  - config_name: java
    data_files:
      - split: dev
        path: java/dev-*
      - split: test
        path: java/test-*
      - split: train
        path: java/train-*
  - config_name: kt
    data_files:
      - split: dev
        path: kt/dev-*
      - split: test
        path: kt/test-*
      - split: train
        path: kt/train-*
  - config_name: mixed
    data_files:
      - split: dev
        path: mixed/dev-*
      - split: test
        path: mixed/test-*
      - split: train
        path: mixed/train-*
  - config_name: py
    data_files:
      - split: dev
        path: py/dev-*
      - split: test
        path: py/test-*
      - split: train
        path: py/train-*

Bug Localization

This is the data for Bug Localization benchmark.

How-to

  1. Since the dataset is private, if you haven't used HF Hub before, add your token via huggingface-cli first:

    huggingface-cli login

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

  3. Load the data via load_dataset:

    from datasets import load_dataset

# Select a configuration from ["py", "java", "kt", "mixed"]
configuration = "py"
# Select a split from ["dev", "train", "test"]
split = "dev"
# Load data
dataset = load_dataset("JetBrains-Research/lca-bug-localization", configuration, split=split)

  4. Load repos via hf_hub_download

    from huggingface_hub import hf_hub_download
from datasets import load_dataset

# Load json with list of repos' .tar.gz file paths
paths_json = load_dataset("JetBrains-Research/lca-bug-localization", data_files="paths.json")

# Load each repo in .tar.gz format, unzip, delete archive
repos = paths_json["repos"][0]

for i, repo_tar_path in enumerate(repos):

    local_repo_tars = hf_hub_download(
        "JetBrains-Research/lca-bug-localization",
        filename=repo_tar_path,
        repo_type="dataset",
        local_dir="local/dir"
    )

    result = subprocess.run(["tar", "-xzf", local_repo_tars, "-C", os.path.join("local/dir", "repos")])
    os.remove(local_repo_tars)

Dataset Structure

TODO: some overall structure or repo

Bug localization data

This section concerns configuration with full data about each commit (no -labels suffix).

Each example has the following fields:

Field Description
repo_owner Bug issue repository owner.
repo_name Bug issue repository name.
issue_url GitHub link to issue
https://github.com/{repo_owner}/{repo_name}/issues/{issue_id}.
pull_url GitHub link to pull request
https://github.com/{repo_owner}/{repo_name}/pull/{pull_id}.
comment_url GitHub link to comment with pull request to issue reference
https://github.com/{repo_owner}/{repo_name}/pull/{pull_id}#issuecomment-{comment_id}.
issue_title Issue title.
issue_body Issue body.
base_sha Pull request base sha.
head_sha Pull request head sha.
diff_url Pull request diff url between base and head sha
https://github.com/{repo_owner}/{repo_name}/compare/{base_sha}...{head_sha}.
diff Pull request diff content.
changed_files List of changed files parsed from diff.
changed_files_exts Dict from changed files extension to count.
changed_files_count Number of changed files.
java_changed_files_count Number of changed .java files.
kt_changed_files_count Number of changed .kt files.
py_changed_files_count Number of changed .py files.
code_changed_files_count Number of changed .java, .kt or .py files.
pull_create_at Data of pull request creation in format yyyy-mm-ddThh:mm:ssZ.
stars Number of repo stars.

Repos data

TODO: describe repos data as .tar.gz archives with list of repos metadata