{"title":"RESTCluster: Automated Crash Clustering for RESTful API","authors":"Yi Liu","doi":"10.1145/3551349.3559511","DOIUrl":null,"url":null,"abstract":"RESTful API has been adopted by many other notable companies to provide cloud services. Quality assurance of RESTful API is essential. Several automated RESTful API testing techniques have been proposed to overcome this problem. However, automated tools often generate a large number of failed test cases. Since validating each test case is a lot of work for developers, automatic failure clustering is a promising solution to help debug cloud services. In this paper, we propose RESTCluster, a two-phase crash clustering approach. The preliminary evaluation result indicates that RESTCluster can achieve 100% precision in different sizes of subjects with a high recall.","PeriodicalId":197939,"journal":{"name":"Proceedings of the 37th IEEE/ACM International Conference on Automated Software Engineering","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 37th IEEE/ACM International Conference on Automated Software Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3551349.3559511","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
RESTful API has been adopted by many other notable companies to provide cloud services. Quality assurance of RESTful API is essential. Several automated RESTful API testing techniques have been proposed to overcome this problem. However, automated tools often generate a large number of failed test cases. Since validating each test case is a lot of work for developers, automatic failure clustering is a promising solution to help debug cloud services. In this paper, we propose RESTCluster, a two-phase crash clustering approach. The preliminary evaluation result indicates that RESTCluster can achieve 100% precision in different sizes of subjects with a high recall.