Reducing UI Complexity Using Use Case Analysis in Adaptive Interfaces

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Publicado no:Computers, Materials, & Continua vol. 85, no. 3 (2025), p. 4607-4628
Autor principal: Qing-Xing Qu
Outros Autores: Zhang, Le, Guo, Fu, Duffy, Vincent G
Publicado em:
Tech Science Press
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022 |a 1546-2218 
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024 7 |a 10.32604/cmc.2025.069245  |2 doi 
035 |a 3270084123 
045 2 |b d20250101  |b d20251231 
100 1 |a Qing-Xing Qu  |u Department of Industrial Engineering, School of Business Administration, Northeastern University, Shenyang, 110167, China 
245 1 |a Reducing UI Complexity Using Use Case Analysis in Adaptive Interfaces 
260 |b Tech Science Press  |c 2025 
513 |a Journal Article 
520 3 |a This study aims to validate the Object-Oriented User Interface Customization (OOUIC) framework by employing Use Case Analysis (UCA) to facilitate the development of adaptive User Interfaces (UIs). The OOUIC framework advocates for User-Centered Design (UCD) methodologies, including UCA, to systematically identify intricate user requirements and construct adaptive UIs tailored to diverse user needs. To operationalize this approach, thirty users of Product Lifecycle Management (PLM) systems were interviewed across six distinct use cases. Interview transcripts were subjected to deductive content analysis to classify UI objects systematically. Subsequently, adaptive UIs were developed for each use case, and their complexity was quantitatively compared against the original system UIs. The results demonstrated a significant reduction in complexity across all adaptive UIs (Mean Difference, MD = 0.11, t(5) = 8.26, p < 0.001), confirming their superior efficiency. The findings validate the OOUIC framework, demonstrating that UCD effectively captures complex requirements for adaptive UI development, while adaptive UIs mitigate interface complexity through object reduction and optimized layout design. Furthermore, UCA and deductive content analysis serve as robust methodologies for object categorization in adaptive UI design. Beyond eliminating redundant elements and prioritizing object grouping, designers can further reduce complexity by adjusting object dimensions and window sizing. This study underscores the efficacy of UCA in developing adaptive UIs and streamlining complex interfaces. Ultimately, UCD proves instrumental in gathering intricate requirements, while adaptive UIs enhance usability by minimizing object clutter and refining spatial organization. 
653 |a Production management 
653 |a Content analysis 
653 |a Design 
653 |a Product life cycle 
653 |a Clutter 
653 |a User interfaces 
653 |a Complexity 
653 |a User requirements 
700 1 |a Zhang, Le  |u AI Department, Quince, Austin, TX 78717, USA 
700 1 |a Guo, Fu  |u Department of Industrial Engineering, School of Business Administration, Northeastern University, Shenyang, 110167, China 
700 1 |a Duffy, Vincent G  |u School of Industrial Engineering, Purdue University, West Lafayette, IN 47907, USA 
773 0 |t Computers, Materials, & Continua  |g vol. 85, no. 3 (2025), p. 4607-4628 
786 0 |d ProQuest  |t Publicly Available Content Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3270084123/abstract/embedded/6A8EOT78XXH2IG52?source=fedsrch 
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