Random GUI testing of android application using behavioral model

Automated GUI testing based on behavioral model is one of the most efficient testing approaches. By mining user usage, test scenarios can be generated based on statistical models such as Markov chain. However, these works require static analysis before starting the exploration which requires too much prerequisites and time. In this work, we propose a behavioralbased GUI testing approach for mobile applications that achieves faster and higher coverage. Our approach does not conduct static analysis. It creates a behavioral model from usage logs by applying a statistical model. The events within the behavioral model is mapped to GUI components in a GUI tree. Finally, it updates the model dynamically to increase the probability of an event that rarely or never occurs when users use the application. We evaluated our approach on three open-source Android applications, and compared it with other approaches. Our approach showed the effectiveness of our tool.