@InProceedings{richardson-kuhn:2017:EMNLP2017Demos,
  author    = {Richardson, Kyle  and  Kuhn, Jonas},
  title     = {Function Assistant: A Tool for NL Querying of APIs},
  booktitle = {Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing: System Demonstrations},
  month     = {September},
  year      = {2017},
  address   = {Copenhagen, Denmark},
  publisher = {Association for Computational Linguistics},
  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.},
  url       = {http://www.aclweb.org/anthology/D17-2012}
}