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tiginamaria commited on
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Update README.md

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@@ -470,7 +470,8 @@ This is the data for **Bug Localization** benchmark as part of LCA.
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  for i, repo_zip_path in enumerate(repos):
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  repo_name = os.path.basename(repo_zip_path).split('.')[0]
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  repo_path = os.path.join(repos_path, repo_name)
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- # Load zip file
 
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  local_repo_zip_path = hf_hub_download(
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  "JetBrains-Research/lca-bug-localization",
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  filename=repo_zip_path,
@@ -478,13 +479,14 @@ This is the data for **Bug Localization** benchmark as part of LCA.
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  local_dir="path/to/zips"
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  )
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- # Unzip file
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  with zipfile.ZipFile(local_repo_zip_path, 'r') as zip_ref:
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  zip_ref.extractall(repo_path)
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  os.remove(local_repo_zip_path)
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  ```
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- Moreover, all process of data loading and streaming is implemented in [HFDataSource](https://github.com/JetBrains-Research/lca-baselines/blob/main/bug_localization/src/baselines/data_sources/hf_data_source.py) which utilize Hugging Face data usage in banchmark infastructure.
 
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  ## Dataset Structure
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@@ -516,9 +518,16 @@ Each example has the following fields:
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  | `kt_changed_files_count` | Number of changed `.kt` files. |
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  | `py_changed_files_count` | Number of changed `.py` files. |
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  | `code_changed_files_count` | Number of changed `.java`, `.kt` or `.py` files. |
 
 
 
 
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  | `pull_create_at` | Data of pull request creation in format yyyy-mm-ddThh:mm:ssZ. |
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- | `stars` | Number of repo stars. |
 
 
 
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  ### Repos data
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- TODO: describe repos data as `.tar.gz` archives with list of repos metadata
 
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  for i, repo_zip_path in enumerate(repos):
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  repo_name = os.path.basename(repo_zip_path).split('.')[0]
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  repo_path = os.path.join(repos_path, repo_name)
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+
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+ # Load repo zip
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  local_repo_zip_path = hf_hub_download(
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  "JetBrains-Research/lca-bug-localization",
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  filename=repo_zip_path,
 
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  local_dir="path/to/zips"
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  )
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+ # Unzip repo
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  with zipfile.ZipFile(local_repo_zip_path, 'r') as zip_ref:
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  zip_ref.extractall(repo_path)
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  os.remove(local_repo_zip_path)
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  ```
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+ Moreover, all process of data loading and streaming is implemented in [HFDataSource](https://github.com/JetBrains-Research/lca-baselines/blob/main/bug_localization/src/baselines/data_sources/hf_data_source.py) which utilize Hugging Face data usage in benchmark infrastructure.
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+ We recommend using it as besides repository cloning process, it returns the state of the repository where bug is reproducable, by extraction repository content for the moment of the base commit sha of fixing pull request.
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  ## Dataset Structure
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  | `kt_changed_files_count` | Number of changed `.kt` files. |
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  | `py_changed_files_count` | Number of changed `.py` files. |
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  | `code_changed_files_count` | Number of changed `.java`, `.kt` or `.py` files. |
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+ | `issue_tokens_count`* | Number of tokens* in issue body (separated by \\n). |
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+ | `issue_lines_count`* | Number of text lines in issue body (separated by \\n). |
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+ | `issue_links_count` | Number of links (\[...\](...)) presented in issue body. |
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+ | `issue_code_blocks_count` | Number of code blocks (\`\`\`...\`\`\`) presented in issue body. |
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  | `pull_create_at` | Data of pull request creation in format yyyy-mm-ddThh:mm:ssZ. |
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+ | `repo_stars` | Number of repo stars. |
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+ | `repo_language` | Main programming language used in the repository. |
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+ | `repo_languages` | All programming languages used in the repository. |
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+ | `repo_license` | Licenses assigned to the repository. |
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  ### Repos data
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+ TODO: describe repos data as `.zip` archives with list of repos metadata