Integrating behavioral semantic analysis in usage-based equivalent tests generation for mobile applications

Abstract

Graphical user interface (GUI) testing is crucial to ensure the expected behaviors of mobile applications (apps). The burgeoning automated usage-based testing seeks to generate simulated human interactions tailored to functional features of apps. However, the difficulties in understanding UI semantics, along with the multiple implementation alternatives, significantly restrict the ability to exercise a specified usage. In this paper, we propose GUEST (Generating Usage-based Equivalent TeSTs), which automates the generation of multiple equivalent tests for GUI usage to help developers more thoroughly test mobile apps' features. GUEST integrates textual information from state pages with the UI structure to express operational GUI widgets with semantic information. It leverages the semantic coverage of edge links within the state transition graph of state-machine encoding for the usage to match canonical screens for the current state page. To exploit behavioral semantics, GUEST treats the state transition graph as a social network and performs centrality analysis to identify key canonical screens in the state transition graph. By utilizing the intimacy between key screens and candidate widgets' reachable screens, GUEST grants higher priority to frequently used and more accessible actions. We evaluate GUEST on desired usages across 22 popular apps and the results reveal that GUEST can successfully exercise the desired usage in 88% of the tests and outperform the state-of-the-art baseline method in both screen and widget classification performance.