@inproceedings{richardson-kuhn-2017-function,
title = "Function Assistant: A Tool for {NL} Querying of {API}s",
author = "Richardson, Kyle and
Kuhn, Jonas",
editor = "Specia, Lucia and
Post, Matt and
Paul, Michael",
booktitle = "Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing: System Demonstrations",
month = sep,
year = "2017",
address = "Copenhagen, Denmark",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/D17-2012",
doi = "10.18653/v1/D17-2012",
pages = "67--72",
abstract = "In this paper, we describe Function Assistant, a lightweight Python-based toolkit for querying and exploring source code repositories using natural language. The toolkit is designed to help end-users of a target API quickly find information about functions through high-level natural language queries, or descriptions. For a given text query and background API, the tool finds candidate functions by performing a translation from the text to known representations in the API using the semantic parsing approach of (Richardson and Kuhn, 2017). Translations are automatically learned from example text-code pairs in example APIs. The toolkit includes features for building translation pipelines and query engines for arbitrary source code projects. To explore this last feature, we perform new experiments on 27 well-known Python projects hosted on Github.",
}
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%0 Conference Proceedings
%T Function Assistant: A Tool for NL Querying of APIs
%A Richardson, Kyle
%A Kuhn, Jonas
%Y Specia, Lucia
%Y Post, Matt
%Y Paul, Michael
%S Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing: System Demonstrations
%D 2017
%8 September
%I Association for Computational Linguistics
%C Copenhagen, Denmark
%F richardson-kuhn-2017-function
%X In this paper, we describe Function Assistant, a lightweight Python-based toolkit for querying and exploring source code repositories using natural language. The toolkit is designed to help end-users of a target API quickly find information about functions through high-level natural language queries, or descriptions. For a given text query and background API, the tool finds candidate functions by performing a translation from the text to known representations in the API using the semantic parsing approach of (Richardson and Kuhn, 2017). Translations are automatically learned from example text-code pairs in example APIs. The toolkit includes features for building translation pipelines and query engines for arbitrary source code projects. To explore this last feature, we perform new experiments on 27 well-known Python projects hosted on Github.
%R 10.18653/v1/D17-2012
%U https://aclanthology.org/D17-2012
%U https://doi.org/10.18653/v1/D17-2012
%P 67-72
Markdown (Informal)
[Function Assistant: A Tool for NL Querying of APIs](https://aclanthology.org/D17-2012) (Richardson & Kuhn, EMNLP 2017)
ACL
- Kyle Richardson and Jonas Kuhn. 2017. Function Assistant: A Tool for NL Querying of APIs. In Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing: System Demonstrations, pages 67–72, Copenhagen, Denmark. Association for Computational Linguistics.