Dataset Open Access

Natural Language-Guided Programming User Study

Heyman, Geert; Huysegems, Rafeal; Justen, Pascal; Van Cutsem, Tom

Dublin Core Export

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<oai_dc:dc xmlns:dc="" xmlns:oai_dc="" xmlns:xsi="" xsi:schemaLocation="">
  <dc:creator>Heyman, Geert</dc:creator>
  <dc:creator>Huysegems, Rafeal</dc:creator>
  <dc:creator>Justen, Pascal</dc:creator>
  <dc:creator>Van Cutsem, Tom</dc:creator>
  <dc:description>In this dataset you find the user study data that was used in the Natural Language-Guided Programming paper, which is accepted for Onward! 2021. A preprint can be found here The dataset consists of the following files:

	benchmark.json contains 201 test cases. Each test case consists of context, a natural language intent and target code. The test cases are intended to evaluate a model that can predict code giving a piece of context code and a natural language intent. The test cases were derived from Jupyter notebooks that were crawled from Github projects with permissive licenses. In the project_metadata field you find information about the original project such as its git url and license.
	predictions-annotated.json contains predictions of the three models used in the paper for 100 test cases in benchmark.json. Each prediction is accompanied with qualitive assesments from three annotators.
	train-index.jsonl is the list of github projects that were used for training the models.
	eval-index.jsonl is a list of github projects that we kept separate for evaluation. The benchmark.json was created from a random subset of the projects in this list.

For more details we refer to the paper.</dc:description>
  <dc:subject>code completion</dc:subject>
  <dc:subject>code prediction</dc:subject>
  <dc:subject>natural language-guided programming</dc:subject>
  <dc:subject>example-centric programming</dc:subject>
  <dc:title>Natural Language-Guided Programming User Study</dc:title>
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