{"title":"Android测试中的配置:它们很重要","authors":"Emily Kowalczyk, Myra B. Cohen, A. Memon","doi":"10.1145/3243218.3243219","DOIUrl":null,"url":null,"abstract":"Android has rocketed to the top of the mobile market thanks in large part to its open source model. Vendors use Android for their devices for free, and companies make customizations to suit their needs. This has resulted in a myriad of configurations that are extant in the user space today. In this paper, we show that differences in configurations, if ignored, can lead to differences in test outputs and code coverage. Consequently, researchers who develop new testing techniques and evaluate them on only one or two configurations are missing a necessary dimension in their experiments and developers who ignore this may release buggy software. In a large study on 18 apps across 88 configurations, we show that only one of the 18 apps studied showed no variation at all. The rest showed variation in either, or both, code coverage and test results. 15% of the 2,000 plus test cases across all of the apps vary, and some of the variation is subtle, i.e. not just a test crash. Our results suggest that configurations in Android testing do matter and that developers need to test using configuration-aware techniques.","PeriodicalId":324676,"journal":{"name":"Proceedings of the 1st International Workshop on Advances in Mobile App Analysis","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":"{\"title\":\"Configurations in Android testing: they matter\",\"authors\":\"Emily Kowalczyk, Myra B. Cohen, A. Memon\",\"doi\":\"10.1145/3243218.3243219\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Android has rocketed to the top of the mobile market thanks in large part to its open source model. Vendors use Android for their devices for free, and companies make customizations to suit their needs. This has resulted in a myriad of configurations that are extant in the user space today. In this paper, we show that differences in configurations, if ignored, can lead to differences in test outputs and code coverage. Consequently, researchers who develop new testing techniques and evaluate them on only one or two configurations are missing a necessary dimension in their experiments and developers who ignore this may release buggy software. In a large study on 18 apps across 88 configurations, we show that only one of the 18 apps studied showed no variation at all. The rest showed variation in either, or both, code coverage and test results. 15% of the 2,000 plus test cases across all of the apps vary, and some of the variation is subtle, i.e. not just a test crash. Our results suggest that configurations in Android testing do matter and that developers need to test using configuration-aware techniques.\",\"PeriodicalId\":324676,\"journal\":{\"name\":\"Proceedings of the 1st International Workshop on Advances in Mobile App Analysis\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-09-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"15\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 1st International Workshop on Advances in Mobile App Analysis\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3243218.3243219\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 1st International Workshop on Advances in Mobile App Analysis","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3243218.3243219","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Android has rocketed to the top of the mobile market thanks in large part to its open source model. Vendors use Android for their devices for free, and companies make customizations to suit their needs. This has resulted in a myriad of configurations that are extant in the user space today. In this paper, we show that differences in configurations, if ignored, can lead to differences in test outputs and code coverage. Consequently, researchers who develop new testing techniques and evaluate them on only one or two configurations are missing a necessary dimension in their experiments and developers who ignore this may release buggy software. In a large study on 18 apps across 88 configurations, we show that only one of the 18 apps studied showed no variation at all. The rest showed variation in either, or both, code coverage and test results. 15% of the 2,000 plus test cases across all of the apps vary, and some of the variation is subtle, i.e. not just a test crash. Our results suggest that configurations in Android testing do matter and that developers need to test using configuration-aware techniques.