Design And Implementation Of Android Software Automated Testing Based On Static Analysis

With the rapid development of mobile Internet,smart phone software quickly integrated into every aspect of people's lives.And the Android operating system,which accounts for more than 80% of the smartphone market,is growing rapidly in both the number of devices and the number of applications.To ensure the correctness and reliability of Android application functionality,it needs to be analyzed and tested.GUI testing is a key point in the Android test.Android GUI's design and development are based on the user events,its state changes are closely related to user events sequence,which makes Android GUI automated Testing has been the difficulties of the industry.It is of great importance to study how to make Android GUI automated testing more effective.At present Android GUI automated testing is mainly divided into random simulated test method and script-based simulated test method.Stochastic simulation test method is based on a completely random simulation to produce test events,which makes test coverage and efficiency too low.Tools based on test scripts,need testers to have a thorough understanding of the program,which makes the workload be comparable to manual testing.In this paper,we propose an optimized approach for Android automation test based on static analysis.By static analysis of Android applications,we build the GUI model of the application,including UI-state transition graph,function call graph and executable event list,to optimize GUI automation testing methods.The optimization is divided into two parts:for the randomly simulating user-event test method,we determine the produce ratio of specific event by UI and event's type and amount;For the precise test methods based on scripts,we related the test api to the corresponding UI and events,to simplify the workload of coding test scripts.With the optimization of test methods through GUI models,we effectively improve the UI coverage of automated test,and help the testers to improve efficiency and optimize code quality.