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--- |
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license: apache-2.0 |
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tags: |
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- git |
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- code |
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size_categories: |
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- 10K<n<100K |
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--- |
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# Dataset Summary |
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GitGoodBench Lite is a subset of 17469 samples for collecting trajectories of AI agents resolving git tasks (see Supported Scenarios) for model training purposes. |
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We support the programming languages Python, Java and Kotlin and the sample types merge conflict resolution and file-commit chain. |
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All data in this dataset are collected from 816 unique, open-source GitHub repositories with permissive licenses |
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that have >= 1000 stars, >= 5 branches, >= 10 contributors and are not a fork or archived. We collected the initial list of repositories using [SEART.](https://seart-ghs.si.usi.ch/) |
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[For further details see our paper.]() |
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# Supported Tasks |
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GitGoodBench Lite contains two types of samples: 'merge' and 'file_commit_chain'. |
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It is important to note that the sample type 'file_commit_chain' can be used for two scenario types: Performing an interactive rebase to clean up the local tree or iteratively |
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generating commits based on the staged, uncommitted changes. |
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## Merge |
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Merge scenarios are contain one or more merge conflicts that occurred during a merge. All merge conflicts are guaranteed to be in a Python, Java or Kotlin file. There are only |
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merges with exactly two parents in our dataset (no octopus merges). |
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A merge scenario looks as follows: |
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``` |
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{ |
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'merge_commit_hash': '9bcf252fb11ec692dfbc152933dddd427098dcc9', |
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'parents': ['5d5df76aa7df56bdbec07c18e063a1125cfd0465', '3bf663778b2a56c614818069043354d4b6d5f156'], |
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'number_of_files_with_merge_conflict': 1, |
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'total_number_of_merge_conflicts': 2, |
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'files_in_merge_conflict': ['models/index_model.py'] |
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} |
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``` |
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Where `merge_commit_hash` contains the ground truth merge commit and the `parents` are the commits during the merge of which the conflict(s) in `files_in_merge_conflict` occurred. |
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## File-Commit Chain |
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File-commit chain scenarios consist of two commits, the oldest and newest commit. In all commits between the `oldest_commit` and `newest_commit` (inclusive) `file` was modified. |
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In total the chain consists of `times_seen_consecutively` commits. The intended use-cases of these scenarios are to evaluate the agent's capacity to create meaningful, cohesive commits or |
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improve the local tree via rebasing. Thus samples of this `sample_type` cover two scenario types. |
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File-commit chains are at least 3 commits long, the file the sample concerns itself with is guaranteed to be of `programming_language` (this is not the case for other potential files in the commits of the sample) and no commit is a merge commit. |
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A `file_commit_chain` scenario looks as follows: |
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``` |
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{ |
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'file': 'torchaudio/transforms/_transforms.py', |
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'branch': 'main', |
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'times_seen_consecutively': 3, |
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'purity': 0.69, |
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'newest_commit': '7ac3e2e237e443baf91dfbf9893fca114c1c6001', |
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'oldest_commit': '3742cebb7dc0f8adf24f4ee1cea368195c448f78' |
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} |
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``` |
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`purity` indicates the relative amount of changes in the chain that occurred solely in `file` and is a heuristic for the difficulty of the scenario. We expect noisier scenarios to be more difficult. |
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# Dataset Structure |
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The following table provides per-field details. Columns marked “Yes” under **Is Metadata?** are those that provide contextual or descriptive information but are not essential to the primary scenario logic. |
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| **Field** | **Type** | **Description** | **Is Metadata?** | |
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|--------------------------|------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------------| |
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| **id** | string | A unique identifier for the dataset entry: <name>-<sample_type>-<running_index> | No | |
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| **name** | string | The repository name, in “owner/repository” format. | No | |
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| **default_branch** | string | The primary or default branch for the repository. | No | |
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| **license** | string | Repository license. | Yes | |
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| **stargazers** | integer | The number of stars on GitHub. | Yes | |
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| **created_at** | string | The repository creation date. | Yes | |
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| **topics** | string | A semicolon-delimited list of topics or tags associated with the repository. | Yes | |
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| **programming_language** | string | The programming language of the sample. Possible values: "java," "python," or "kotlin." | No | |
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| **scenario** | string | A JSON string describing specific scenario data (e.g., merge-conflict details, parent commits). | No | |
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| **sample_type** | string | The type of sample. Possible values: "merge" or "file_commit_chain." | No | |
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| **project_size** | string | Estimated size based on lines of code. Possible values: "tiny," "small," "medium," "large," or "huge." | Yes | |
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| **difficulty** | string | The complexity level of the scenario. Possible values: "easy," "medium," or "hard." | Yes | |
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**Note**: |
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- Fields marked as **Is Metadata? = Yes** provide contextual information (e.g., project stats, licensing) rather than forming the core logic of a scenario. |
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- Fields marked **No** represent the primary data for the scenario. Use them to inform or categorize the scenario type and project details. |
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# Dataset statistics |
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We provide some statistics on the diversity of our dataset with respect to repositories, programming languages and merge conflict resolution samples. |
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## Dataset Skew |
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The below statistics show that our dataset does not exhibit an extreme skew towards some repositories and is relatively well balanced with respect to source repositories. |
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### Distribution Statistics |
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- Total number of repositories analyzed: 816 |
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- Average (mean) samples per repository: 21.4 |
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- Standard deviation (std): 48.8 |
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- Minimum (min): 1 |
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- 25th percentile (25%): 2 |
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- Median (50%): 6 |
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- 75th percentile (75%): 18 |
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- Maximum (max): 644 |
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### Top-10 Repositories by Sample Count |
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| Repository | Percentage of Total Samples | |
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|------------------------------------------|----------------------------:| |
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| zulip/zulip | 3.69% | |
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| trinodb/trino | 2.47% | |
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| wandb/wandb | 2.46% | |
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| facebook/litho | 2.16% | |
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| oss-review-toolkit/ort | 1.96% | |
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| apache/tomcat | 1.94% | |
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| nvidia/nemo | 1.76% | |
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| h2oai/h2ogpt | 1.32% | |
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| conan-io/conan | 1.30% | |
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| huggingface/transformers | 1.05% | |
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### Distribution of Programming Languages |
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We do however note a severe skew towards Python and Java with only 3.8% of samples being Kotlin. |
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| Programming Language | Count | Percentage | |
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|----------------------|--------:|-----------:| |
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| python | 10985 | 62.82% | |
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| java | 5881 | 33.67% | |
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| kotlin | 603 | 3.45% | |
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## Difficulty Distribution for "merge" Scenarios |
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| Difficulty | Proportion | |
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|------------|-----------:| |
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| easy | 0.516466 | |
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| hard | 0.299672 | |
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| medium | 0.183861 | |
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**Languages** We note that the text data in this dataset consists mostly of: commit messages, comments and is primarily in English. We do however not filter for any human languages explcitly. |