NLP2API:使用众包知识和超大数据分析的代码搜索查询重构

2018 IEEE International Conference on Software Maintenance and Evolution (ICSME) Pub Date : 2018-09-01 DOI:10.1109/ICSME.2018.00086

M. M. Rahman, C. Roy

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引用次数: 10

摘要

软件开发人员经常为代码搜索发出通用自然语言(NL)查询。不幸的是，由于词汇不匹配的问题，这样的查询通常无法在当代代码(或web)搜索引擎中得到任何相关的结果。在我们的技术研究论文(在ICSME 2018上被接受)中，我们提出了一种技术- nlp2api -该技术使用来自Stack Overflow问答网站的众包知识和超大数据分析来重新制定这种自然语言查询。在本文中，我们讨论了由我们的工作产生的所有工件，并提供了下载和验证它们的必要细节。

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NLP2API: Query Reformulation for Code Search Using Crowdsourced Knowledge and Extra-Large Data Analytics

Software developers frequently issue generic natural language (NL) queries for code search. Unfortunately, such queries often do not lead to any relevant results with contemporary code (or web) search engines due to vocabulary mismatch problems. In our technical research paper (accepted at ICSME 2018), we propose a technique–NLP2API–that reformulates such NL queries using crowdsourced knowledge and extra-large data analytics derived from Stack Overflow Q & A site. In this paper, we discuss all the artifacts produced by our work, and provide necessary details for downloading and verifying them.

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2018 IEEE International Conference on Software Maintenance and Evolution (ICSME)

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