Neat: Mobile App Layout Similarity Comparison based on Graph Convolutional Networks


A wide variety of device models, screen resolutions and operating systems have emerged with recent advances in mobile devices. As a result, the graphical user interface (GUI) layout in mobile apps has become increasingly complex due to this market fragmentation, with rapid iterations being the norm. Testing page layout issues under these circumstances hence becomes a resource-intensive task, requiring significant manpower and effort due to the vast number of device models and screen resolution adaptations. One of the most challenging issues to cover manually is multi-model and cross-version layout verification for the same GUI page. To address this issue, we propose Neat, a non-intrusive end-to-end mobile app layout similarity measurement tool that utilizes computer vision techniques for GUI element detection, layout feature extraction, and similarity metrics. Our empirical evaluation and industrial application have demonstrated that our approach is effective in improving the efficiency of layout assertion testing and ensuring application quality.

In proceedings of the ACM International Conference on the Foundations of Software Engineering (FSE 2024)
Chao Peng
Chao Peng
Senior Researcher

My research interests include Software Testing, Program Repair and Compilers.