November 28, 2021 Dataset Open Access

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

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{
  "description": "<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>", 
  "license": "https://creativecommons.org/licenses/by/4.0/legalcode", 
  "creator": [
    {
      "affiliation": "Heidelberg University", 
      "@type": "Person", 
      "name": "Le, Kim Tuyen"
    }, 
    {
      "affiliation": "Heidelberg University", 
      "@type": "Person", 
      "name": "Rashidi, Gabriel"
    }, 
    {
      "affiliation": "Heidelberg University", 
      "@type": "Person", 
      "name": "Andrzejak, Artur"
    }
  ], 
  "url": "https://zenodo.org/record/5733013", 
  "datePublished": "2021-11-28", 
  "keywords": [
    "code completion", 
    "accuracy evaluation", 
    "code token types"
  ], 
  "@context": "https://schema.org/", 
  "distribution": [
    {
      "contentUrl": "https://zenodo.org/api/files/af5de9a9-a02a-4445-9ce7-c15c48aabb9b/CT3-dataset-journal-20211128.zip", 
      "encodingFormat": "zip", 
      "@type": "DataDownload"
    }
  ], 
  "identifier": "https://doi.org/10.5281/zenodo.5733013", 
  "@id": "https://doi.org/10.5281/zenodo.5733013", 
  "@type": "Dataset", 
  "name": "A Code Token Type Taxonomy-enhanced dataset with pre-computed token types for Python150k"
}