A Model-Based Approach to Mobile Application Testing

Abstract

Abstract Modeling the automated testing of mobile applications is a crucial aspect of mobile application automation testing. Due to the varied styles and complex interactions of mobile applications, automated modeling methods are urgently required, particularly in the context of their short development cycles, large numbers, and fast version iterations and updates. In this paper, we address the challenge of exploring mobile application behavior and state based on robotic testing environment without invading the application interior, and propose a method for automated exploration of GUI components and GUI events of applications combined with application domain knowledge to generate mobile application GUI semantic test models. Our results show that the proposed semantic model achieves 70.6% and 82.4% defect detection rate in the robot vision environment and simulation environment, respectively. Compared with the comparative testing method that can only find application crash defects, our method can explore both crash defects and functional anomalies with the application semantic understanding and domain knowledge, thereby extending the automated mobile application functional testing capability of mobile applications. In response to the limitations of mobile application automated testing modeling mentioned above, this paper introduces an automated testing method based on semantic models. It uses the proposed semantic testing model to guide the purposeful exploration of the tested application’s states. Subsequently, it generates positive and negative test cases based on the domain knowledge associated with the semantic model. This modeling approach leverages domain models in the mobile application field to conduct automated modeling tests imbued with functional significance, guided by domain knowledge. This optimization aims to address the shortcomings of current automated testing, particularly in terms of model reuse and test expansion.