November 28, 2021 Dataset Open Access

Le, Kim Tuyen; Rashidi, Gabriel; Andrzejak, Artur

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{
  "publisher": "Zenodo", 
  "DOI": "10.5281/zenodo.5733013", 
  "author": [
    {
      "family": "Le, Kim Tuyen"
    }, 
    {
      "family": "Rashidi, Gabriel"
    }, 
    {
      "family": "Andrzejak, Artur"
    }
  ], 
  "issued": {
    "date-parts": [
      [
        2021, 
        11, 
        28
      ]
    ]
  }, 
  "abstract": "<p>Code Token Type Taxonomy (CT3) is a methodology for refined evaluation of ML-based code completion approaches.</p>\n\n<p>We published the&nbsp;CT3-enhanced dataset with pre-computed token types for each token in the <a href=\"https://www.sri.inf.ethz.ch/py150\">Python150k dataset</a>.</p>\n\n<p>The dataset was obtained from&nbsp;an empirical study of the below paper:</p>\n\n<p>Kim Tuyen Le, Gabriel Rashidi, and Artur Andrzejak. A Methodology for Refined Evaluation of ML-based Code Completion Approaches. In <em>Special Issue on Programming Language Processing, Data Mining and Knowledge Discovery</em>.</p>\n\n<p>Please read the README.txt file for detailed information of structuring the enhanced dataset.</p>", 
  "title": "A Code Token Type Taxonomy-enhanced dataset with pre-computed token types for Python150k", 
  "type": "dataset", 
  "id": "5733013"
}