Dataset Open Access

A Dataset of Pull Requests and A Trained Random Forest Model for predicting Pull Request Acceptance

Tapajit Dey; Audris Mockus


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{
  "publisher": "Zenodo", 
  "DOI": "10.5281/zenodo.3858046", 
  "author": [
    {
      "family": "Tapajit Dey"
    }, 
    {
      "family": "Audris Mockus"
    }
  ], 
  "issued": {
    "date-parts": [
      [
        2020, 
        5, 
        26
      ]
    ]
  }, 
  "abstract": "<p>A Curated Dataset of 470,925 pull requests for 3349 popular NPM packages, description of the variables, code snippet for creating a Random Forest model for predicting pull request acceptance, and a pre-trained&nbsp;&nbsp;Random Forest model (in R). The dataset is for the ESEM-2020 paper: &quot;Impact of Technical and Social Factors on Pull Request Quality for the NPM Ecosystem&quot; (<a href=\"https://arxiv.org/abs/2007.04816\">https://arxiv.org/abs/2007.04816</a>).&nbsp;</p>\n\n<p>Citation:</p>\n\n<pre>@inproceedings{dey2020effect,\n  title={Effect of technical and social factors on pull request quality for the npm ecosystem},\n  author={Dey, Tapajit and Mockus, Audris},\n  booktitle={Proceedings of the 14th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM)},\n  pages={1--11},\n  year={2020}\n}</pre>", 
  "title": "A Dataset of Pull Requests and A Trained Random Forest Model for predicting Pull Request Acceptance", 
  "type": "dataset", 
  "id": "3858046"
}
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