Xia Zeng, Dengfeng Li, Wujie Zheng, Fan Xia, Yuetang Deng, Wing Lam, Wei Yang, Tao Xie
{"title":"Automated test input generation for Android: are we really there yet in an industrial case?","authors":"Xia Zeng, Dengfeng Li, Wujie Zheng, Fan Xia, Yuetang Deng, Wing Lam, Wei Yang, Tao Xie","doi":"10.1145/2950290.2983958","DOIUrl":null,"url":null,"abstract":"Given the ever increasing number of research tools to automatically generate inputs to test Android applications (or simply apps), researchers recently asked the question \"Are we there yet?\" (in terms of the practicality of the tools). By conducting an empirical study of the various tools, the researchers found that Monkey (the most widely used tool of this category in industrial practices) outperformed all of the research tools that they studied. In this paper, we present two significant extensions of that study. First, we conduct the first industrial case study of applying Monkey against WeChat, a popular messenger app with over 762 million monthly active users, and report the empirical findings on Monkey's limitations in an industrial setting. Second, we develop a new approach to address major limitations of Monkey and accomplish substantial code-coverage improvements over Monkey, along with empirical insights for future enhancements to both Monkey and our approach.","PeriodicalId":20532,"journal":{"name":"Proceedings of the 2016 24th ACM SIGSOFT International Symposium on Foundations of Software Engineering","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"83","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2016 24th ACM SIGSOFT International Symposium on Foundations of Software Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2950290.2983958","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 83
Abstract
Given the ever increasing number of research tools to automatically generate inputs to test Android applications (or simply apps), researchers recently asked the question "Are we there yet?" (in terms of the practicality of the tools). By conducting an empirical study of the various tools, the researchers found that Monkey (the most widely used tool of this category in industrial practices) outperformed all of the research tools that they studied. In this paper, we present two significant extensions of that study. First, we conduct the first industrial case study of applying Monkey against WeChat, a popular messenger app with over 762 million monthly active users, and report the empirical findings on Monkey's limitations in an industrial setting. Second, we develop a new approach to address major limitations of Monkey and accomplish substantial code-coverage improvements over Monkey, along with empirical insights for future enhancements to both Monkey and our approach.