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--- |
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license: mit |
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configs: |
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- config_name: default |
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data_files: |
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- split: train |
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path: data/train-* |
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- split: test |
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path: data/test-* |
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- split: validation |
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path: data/validation-* |
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dataset_info: |
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features: |
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- name: CommitHash |
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dtype: string |
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- name: NewPath |
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dtype: string |
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- name: Diff |
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dtype: string |
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- name: FaultInducingLabel |
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dtype: int64 |
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splits: |
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- name: train |
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num_bytes: 116120391 |
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num_examples: 207464 |
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- name: test |
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num_bytes: 38526893 |
|
num_examples: 69155 |
|
- name: validation |
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num_bytes: 38411094 |
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num_examples: 69155 |
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download_size: 65354656 |
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dataset_size: 193058378 |
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--- |
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# Dataset Card for TechDebt |
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This dataset was generated from [The Technical Debt Dataset](https://github.com/clowee/The-Technical-Debt-Dataset) created by Lenarduzzi, et al. and the citation is down below. |
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## Dataset Details and Structure |
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The labels for the dataset were provided by the SZZ algorithm cited by the paper and matched to the diff in the commit where the technical debt was located. This diff was then cleaned to only include the lines of code added. |
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## Bias, Risks, and Limitations |
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Beware of the data imbalance if you would like to use the dataset. Also, the queries used to extract this data are still being checked over to ensure correctness. |
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## Recommendations |
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Changes are constantly being made to this dataset to make it better. Please be aware when you use it. |
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## References |
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Valentina Lenarduzzi, Nyyti Saarimäki, Davide Taibi. The Technical Debt Dataset. Proceedings for the 15th Conference on Predictive Models and Data Analytics in Software Engineering. Brazil. 2019. |
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