TY - GEN
T1 - An Empirical Study on UI Overlap in OpenHarmony Applications
AU - Liu, Farong
AU - Zhou, Mingyi
AU - Li, Li
N1 - Publisher Copyright:
© 2025 IEEE.
PY - 2025
Y1 - 2025
N2 - UI overlap is a phenomenon where one UI component visually covers another. While this overlap is necessary to construct rich visual hierarchies, it is also a root cause of usability issues and performance bottlenecks. However, a systematic, data-driven understanding of its prevalence and patterns has been lacking. To bridge this gap, we conduct the first large-scale empirical study on UI overlap in the OpenHarmony ecosystem. We analyze 100 popular apps, classifying 33,262,624 overlap instances through a novel three-tiered taxonomy. Our findings reveal that high-cost occlusion is a critical and previously hard-to-detect performance defect where resource-intensive components are rendered while visually obscured. We propose HCO-Eye, an innovative tool that leverages multimodal vision-language models (VLMs) to automatically detect such issues, successfully identifying 34 high-cost occlusion cases in commercial apps. Our study not only provides the first comprehensive understanding of UI overlap in OpenHarmony but also offers a practical tool to automatically diagnose complex performance-related UI bugs. Our tools are publicly available.
AB - UI overlap is a phenomenon where one UI component visually covers another. While this overlap is necessary to construct rich visual hierarchies, it is also a root cause of usability issues and performance bottlenecks. However, a systematic, data-driven understanding of its prevalence and patterns has been lacking. To bridge this gap, we conduct the first large-scale empirical study on UI overlap in the OpenHarmony ecosystem. We analyze 100 popular apps, classifying 33,262,624 overlap instances through a novel three-tiered taxonomy. Our findings reveal that high-cost occlusion is a critical and previously hard-to-detect performance defect where resource-intensive components are rendered while visually obscured. We propose HCO-Eye, an innovative tool that leverages multimodal vision-language models (VLMs) to automatically detect such issues, successfully identifying 34 high-cost occlusion cases in commercial apps. Our study not only provides the first comprehensive understanding of UI overlap in OpenHarmony but also offers a practical tool to automatically diagnose complex performance-related UI bugs. Our tools are publicly available.
KW - dynamic analysis
KW - openharmony
KW - performance analysis
KW - ui overlap
KW - usability
UR - https://www.scopus.com/pages/publications/105034648314
U2 - 10.1109/ASE63991.2025.00274
DO - 10.1109/ASE63991.2025.00274
M3 - 会议稿件
AN - SCOPUS:105034648314
T3 - Proceedings - 2025 40th IEEE/ACM International Conference on Automated Software Engineering, ASE 2025
SP - 3322
EP - 3333
BT - Proceedings - 2025 40th IEEE/ACM International Conference on Automated Software Engineering, ASE 2025
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2025 40th IEEE/ACM International Conference on Automated Software Engineering, ASE 2025
Y2 - 16 November 2025 through 20 November 2025
ER -