The use of mobile apps is increasingly widespread, and much effort is put into testing these apps to make sure they behave as intended. To reduce this effort, and thus the overall cost of mobile app testing, we propose AppTestMigrator, a technique for migrating test cases between apps in the same category (e.g., banking apps). The intuition behind AppTestMigrator is that many apps share similarities in their functionality, and these similarities often result in conceptually similar user interfaces (through which that functionality is accessed). AppTestMigrator leverages these commonalities between user interfaces to migrate existing tests written for an app to another similar app. Specifically, given (1) a test case for an app (source app) and (2) a second app (target app), AppTestMigrator attempts to automatically transform the sequence of events and oracles in the test for the source app to events and oracles for the target app. We implemented AppTestMigrator for Android mobile apps and evaluated it on a set of randomly selected apps from the Google Play Store in four different categories. Our initial results are promising, support our intuition that test migration is possible, and motivate further research in this direction.
Tue 12 Nov
10:40 - 11:00 Talk | Test Transfer Across Mobile Apps Through Semantic Mapping Jun-Wei LinUniversity of California, Irvine, Reyhaneh JabbarvandUniversity of California, Irvine, Sam MalekUniversity of California, Irvine | |||||||||||||||||||||||||||||||||||||||||
11:00 - 11:20 Talk | Test Migration Between Mobile Apps with Similar Functionality | |||||||||||||||||||||||||||||||||||||||||
11:20 - 11:40 Talk | DaPanda: Detecting Aggressive Push Notification in Android Apps Tianming LiuBeijing University of Posts and Telecommunications, China, Haoyu WangBeijing University of Posts and Telecommunications, China, Li LiMonash University, Australia, Guangdong BaiGriffith University, Yao GuoPeking University, Guoai Xu Beijing University of Posts and Telecommunications | |||||||||||||||||||||||||||||||||||||||||
11:40 - 12:00 Talk | Automatic, highly accurate app permission recommendation Zhongxin LiuZhejiang University, Xin XiaMonash University, David LoSingapore Management University, John GrundyMonash University Link to publication | |||||||||||||||||||||||||||||||||||||||||
12:00 - 12:10 Demonstration | LIRAT: Layout and Image Recognition Driving Automated Mobile Testing of Cross-Platform Shengcheng YuNanjing University, China, Chunrong FangNanjing University, Yang FengUniversity of California, Irvine, Wenyuan ZhaoNanjing University, Zhenyu ChenNanjing University | |||||||||||||||||||||||||||||||||||||||||
12:10 - 12:20 Demonstration | Humanoid: A Deep Learning-based Approach to Automated Black-box Android App Testing Yuanchun LiPeking University, Ziyue YangPeking University, Yao GuoPeking University, Xiangqun ChenPeking University |