众包
上传
计算机科学
相似性(几何)
考试(生物学)
特征(语言学)
众包软件开发
过程(计算)
情报检索
数据挖掘
人工智能
万维网
软件
软件开发
图像(数学)
操作系统
哲学
古生物学
软件建设
程序设计语言
生物
语言学
作者
Lizhi Cai,Naiqi Wang,Mingang Chen,Jin Wang,Jilong Wang,Jiayu Gong
标识
DOI:10.1109/qrs-c55045.2021.00018
摘要
In recent years, a new testing method based on the concept of crowdsourcing has made great progress. Developers upload the project to the crowdsourcing test platform and recruit a large number of crowdsourcing workers for testing, so that the testing process has higher test adequacy, faster testing speed and lower testing cost. However, the test reports submitted after the test have serious problems such as large quantity and high similarity, resulting in the failure to achieve the expected results. Based on the method of feature fusion, this paper integrates the text description information, bug type information and screenshot information of crowdsourcing test reports, clusters crowdsourcing test reports through the calculation of similarity between reports, and finally achieves better results.
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