Improving source code search with natural language phrasal representations of method signatures
Improving source code search with natural language phrasal representations of method signatures
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DOI：
10.1109/ase.2011.6100115
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发表时间：
2011-11
期刊：
影响因子：
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通讯作者：
Emily Hill;L. Pollock;K. Vijay-Shanker
中科院分区：
文献类型：
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作者：
Emily Hill;L. Pollock;K. Vijay-Shanker
随着软件的不断增长，为维护任务定位代码变得越来越困难。软件搜索工具帮助开发人员找到与其维护任务相关的源代码。成功的搜索工具面临的一个主要挑战是，当用户的查询包含具有多种含义的单词或在整个程序中频繁出现的单词时，如何定位相关代码。传统的搜索技术，单独对待每个词，无法区分相关和不相关的方法在这些条件下。在本文中，我们提出了一种新的搜索技术，使用的信息，如查询词的位置和它的语义角色来计算相关性。我们的评估表明，这种方法比其他三种最先进的搜索技术更有效。
As software continues to grow, locating code for maintenance tasks becomes increasingly difficult. Software search tools help developers find source code relevant to their maintenance tasks. One major challenge to successful search tools is locating relevant code when the user's query contains words with multiple meanings or words that occur frequently throughout the program. Traditional search techniques, which treat each word individually, are unable to distinguish relevant and irrelevant methods under these conditions. In this paper, we present a novel search technique that uses information such as the position of the query word and its semantic role to calculate relevance. Our evaluation shows that this approach is more consistently effective than three other state of the art search techniques.