FuncDroid: Towards Inter-Functional Flows for Comprehensive Mobile App GUI Testing

• URL: http://arxiv.org/abs/2602.12834v1
• Date: Fri, 13 Feb 2026 11:40:02 GMT
• Title: FuncDroid: Towards Inter-Functional Flows for Comprehensive Mobile App GUI Testing
• Authors: Jinlong He, Changwei Xia, Binru Huang, Jiwei Yan, Jun Yan, Jian Zhang,
• Abstract summary: We introduce an inter-functional-flow-oriented GUI testing approach with the dual goals of precise model construction and deep bug detection.<n>By combining two complementary test-generation views, it can adaptively refine functional boundaries and systematically explore inter-functional flows.<n>We implement our approach in a tool called FuncDroid, and evaluate it on two benchmarks: (1) a widely-used open-source benchmark with 50 reproducible crash bugs and (2) a diverse set of 52 popular commercial apps.
• Score: 6.346121677855558
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: As mobile application (app) functionalities grow increasingly complex and their iterations accelerate, ensuring high reliability presents significant challenges. While functionality-oriented GUI testing has attracted growing research attention, existing approaches largely overlook interactions across functionalities, making them ineffective at uncovering deep bugs hidden in inter-functional behaviors. To fill this gap, we first design a Functional Flow Graph (FFG), a behavioral model that explicitly captures an app's functional units and their inter-functional interactions. Based on the FFG, we further introduce an inter-functional-flow-oriented GUI testing approach with the dual goals of precise model construction and deep bug detection. This approach is realized through a long-short-term-view-guided testing process. By combining two complementary test-generation views, it can adaptively refine functional boundaries and systematically explore inter-functional flows under diverse triggering conditions. We implement our approach in a tool called FuncDroid, and evaluate it on two benchmarks: (1) a widely-used open-source benchmark with 50 reproducible crash bugs and (2) a diverse set of 52 popular commercial apps. Experimental results demonstrate that FuncDroid significantly outperforms state-of-the-art baselines in both coverage (+28%) and bug detection number (+107%). Moreover, FuncDroid successfully uncovers 18 previously unknown non-crash functional bugs in commercial apps, confirming its practical effectiveness.

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