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Code Search Based on Alteration Intent
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AI
DOI：10.1109/ACCESS.2019.2913560.png)
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摘要
En 中文
Code search is to retrieve the method according to the user needs. Many people think of the query as the only one to reflect the user needs. So they start with the query and find the synonyms, semantically similar to the query terms, for query expansion. However, they overlook a fact: the retrieved methods still need to be altered because it does not meet the user needs directly. This implies that the alteration made in the retrieved methods also reflects the user needs. In this paper, we start with the alteration intent (the possible alterations after retrieving methods) and propose to predict the alteration intent and use it for query expansion. The experiment results show that our approach outperforms CodeHow, the approach to use APIs for query expansion, by 59.8% with a precision score of 0.815.
Keyword:
Code search
query expansion
alteration intent
program context
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
3.6
论文数:
9.8W
被引数:
29.4W
机构
引用论文
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分享收藏分享收藏AN INFORMATION-RETRIEVAL APPROACH FOR AUTOMATICALLY CONSTRUCTING SOFTWARE LIBRARIES一种自动构建软件库的信息检索方法
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