Deep learning-based open API recommendation for Mashup development  

作　　者：Ye WANG Junwu CHEN Qiao HUANG Xin XIA Bo JIANG 

机构地区：[1]School of Computer and Information Engineering,Zhejiang Gongshang University,Hangzhou 310018,China [2]Software Engineering Application Technology Lab,Huawei,Hangzhou 310005,China

出　　处：《Science China(Information Sciences)》2023年第7期90-107,共18页中国科学（信息科学）（英文版）

基　　金：supported by National Science Foundation of Zhejiang Province(Grant Nos.LY21F020011,LY20F020027,LY19F020003);Key Research and Development Program of Zhejiang Province(Grant No.2021C01162);National Natural Science Foundation of China(Grant No.61672459)。

摘　　要：Mashup developers often need to find open application programming interfaces(APIs)for their composition application development.Although most enterprises and service organizations have encapsulated their businesses or resources online as open APIs,finding the right high-quality open APIs is not an easy task from a library with several open APIs.To solve this problem,this paper proposes a deep learning-based open API recommendation(DLOAR)approach.First,the hierarchical density-based spatial clustering of applications with a noise topic model is constructed to build topic models for Mashup clusters.Second,developers’requirement keywords are extracted by the Text Rank algorithm,and the language model is built.Third,a neural network-based three-level similarity calculation is performed to find the most relevant open APIs.Finally,we complement the relevant information of open APIs in the recommended list to help developers make better choices.We evaluate the DLOAR approach on a real dataset and compare it with commonly used open API recommendation approaches:term frequency-inverse document frequency,latent dirichlet allocation,Word2Vec,and Sentence-BERT.The results show that the DLOAR approach has better performance than the other approaches in terms of precision,recall,F1-measure,mean average precision,and mean reciprocal rank.

关 键 词：Mashup development open API recommendation deep learning neural network service discovery 

分 类 号：TP391.3[自动化与计算机技术—计算机应用技术] TP18[自动化与计算机技术—计算机科学与技术]