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@@ -4,19 +4,19 @@ configs:
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  data_files:
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  - split: test
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  path: data/python/*.json
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- license: apache-2.0
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  ---
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- # ๐ŸŸ๏ธ Long Code Arena (CI Fixing)
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- > ๐Ÿ› ๏ธ CI Fixing: given logs of a failed GitHub Actions workflow and the corresponding repository shapshot, fix the
 
 
 
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  > repository contents in order to make the workflow pass.
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- This is the benchmark for **CI Fixing** task as part of
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- ๐ŸŸ๏ธ [**Long Code Arena** benchmark](https://huggingface.co/spaces/JetBrains-Research/long-code-arena).
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- To score your model on this dataset, you can use **CI Fixing benchmark**
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- (https://github.com/JetBrains-Research/lca-baselines/tree/main/ci-fixing/ci-fixing-benchmark)
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  ## How-to
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@@ -36,7 +36,7 @@ To score your model on this dataset, you can use **CI Fixing benchmark**
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  ```
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  Note that all the data we have is considered to be in the test split.
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- **NOTE**: If you encounter any errors with loading the dataset on Windows, update the datasets library (was tested on datasets==2.16.1)
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  ## Dataset Structure
@@ -44,9 +44,9 @@ To score your model on this dataset, you can use **CI Fixing benchmark**
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  This dataset contains logs of the failed GitHub Action workflows for some commits
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  followed by the commit that passes the workflow successfully.
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- Note that, unlike many other ๐ŸŸ Long Code Arena datasets, this dataset doesn't contain repositories.
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- * Our [CI Fixing benchmark](https://github.com/JetBrains-Research/lca-baselines/tree/main/ci-fixing/ci-fixing-benchmark) clones the necessary repos to the user's local machine. The user should run
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  their model to
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  fix the failing CI workflows, and the benchmark will push commits to GitHub, returning the results of the workflow
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  runs
@@ -60,14 +60,14 @@ Each example has the following fields:
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  | Field | Description |
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  |---------------------|------------------------------------------------------------------------------------------------------------------------------|
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  | `contributor` | Username of the contributor that committed changes |
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- | `difficulty` | Difficulty of the problem (assessor-based. 0 means that fix requires only the code formatting) |
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  | `diff` | Contents of the diff between the failed and the successful commits |
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  | `head_branch` | Name of the original branch that the commit was pushed at |
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  | `id` | Unique ID of the datapoint |
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- | `language` | Main language of the repo |
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  | `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) |
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- | `repo_name` | Name of the original repo (second part of the `owner/name` on GitHub) |
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- | `repo owner` | Owner of the original repo (first part of the `owner/name` on GitHub) |
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  | `sha_fail` | SHA of the failed commit |
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  | `sha_success` | SHA of the successful commit |
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  | `workflow` | Contents of the workflow file |
 
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  data_files:
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  - split: test
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  path: data/python/*.json
 
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  ---
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+ # ๐ŸŸ๏ธ Long Code Arena (CI builds repair)
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+ This is the benchmark for CI builds repair task as part of the
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+ ๐ŸŸ๏ธ [Long Code Arena benchmark](https://huggingface.co/spaces/JetBrains-Research/long-code-arena).
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+
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+ > ๐Ÿ› ๏ธ CI build repair: given the logs of a failed GitHub Actions workflow and the corresponding repository shapshot, fix the
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  > repository contents in order to make the workflow pass.
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+ All the data is collected from repositories published under permissive licenses (MIT, Apache-2.0, BSD-3-Clause, and BSD-2-Clause). The datapoints can be removed upon request.
 
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+ To score your model on this dataset, you can use [**CI build repair benchmark**](https://github.com/JetBrains-Research/lca-baselines/tree/main/ci-fixing/ci-fixing-benchmark).
 
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  ## How-to
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  ```
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  Note that all the data we have is considered to be in the test split.
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+ **NOTE**: If you encounter any errors with loading the dataset on Windows, update the `datasets` library (was tested on `datasets==2.16.1`)
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  ## Dataset Structure
 
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  This dataset contains logs of the failed GitHub Action workflows for some commits
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  followed by the commit that passes the workflow successfully.
46
 
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+ Note that, unlike other ๐ŸŸ๏ธ Long Code Arena datasets, this dataset does not contain repositories.
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+ * Our [CI builds repair benchmark](https://github.com/JetBrains-Research/lca-baselines/tree/main/ci-fixing/ci-fixing-benchmark) clones the necessary repos to the user's local machine. The user should run
50
  their model to
51
  fix the failing CI workflows, and the benchmark will push commits to GitHub, returning the results of the workflow
52
  runs
 
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  | Field | Description |
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  |---------------------|------------------------------------------------------------------------------------------------------------------------------|
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  | `contributor` | Username of the contributor that committed changes |
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+ | `difficulty` | Difficulty of the problem (assessor-based. 0 means that the fix requires only the code formatting) |
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  | `diff` | Contents of the diff between the failed and the successful commits |
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  | `head_branch` | Name of the original branch that the commit was pushed at |
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  | `id` | Unique ID of the datapoint |
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+ | `language` | Main language of the repository |
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  | `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) |
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+ | `repo_name` | Name of the original repository (second part of the `owner/name` on GitHub) |
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+ | `repo owner` | Owner of the original repository (first part of the `owner/name` on GitHub) |
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  | `sha_fail` | SHA of the failed commit |
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  | `sha_success` | SHA of the successful commit |
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  | `workflow` | Contents of the workflow file |