基于wi - wmd的API推荐

Pub Date : 2021-10-01 DOI:10.4018/ijcini.20211001.oa16

Wanzhi Wen, Shiqiang Wang, Bingqing Ye, XingYu Zhu, Yitao Hu, Xiaohong Lu, Bin Zhang

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引用次数: 0

摘要

基于现有api提高软件开发效率是软件工程领域的研究热点之一。理解和学习大型软件库中的这么多API并不容易，软件开发人员更愿意只提供需求描述来获得正确的API。为了解决这一问题，本文提出了一种基于改进的相似度计算算法WII-WMD的API推荐方法。该方法首先对文本进行结构化，然后充分挖掘文本中的语义信息。最后，计算用户查询问题与API文档中描述的信息之间的相似度。实验结果表明，基于wi - wmd的API推荐可以提高API推荐系统的效率。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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API Recommendation Based on WII-WMD

Improving software development efficiency based on existing APIs is one of the hot researches in software engineering. Understanding and learning so many APIs in large software libraries is not easy and software developers prefer to provide only requirements descriptions to get the right API. In order to solve this problem, this paper proposes an API recommendation method based on WII-WMD, an improved similarity calculation algorithm. This method firstly structures the text, and then fully mines the semantic information in the text. Finally, it calculates the similarity between the user's query problem and the information described in the API document. The experiment results show that the API recommendation based on WII-WMD can improve the efficiency of the API recommendation system.

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