Quality Assessment of Web and APP Design Patterns

Abstract—To respond to the needs of platform users on mobile devices in recent years, several types of web and mobile application software design patterns, including responsive web design (RWD), adaptive website design (AWD), Separate URLs (M.dot), and mobile application software (APP) have been proposed. However, it is difficult for platform owners and developers to decide which design pattern is suitable for them. Therefore, this study explored the literature on the quality assessment indicators of websites and web applications and proposed three quality facets based on the quality inspection project of the website of the National Development Council (NDC). There were three quality facets and a total of 14 quality indicators. This study further chose six sample platforms of three types of social media, news media, and e-commerce based on the network traffic analysis platform. After evaluation and testing, this study analyzed the evaluation results of different design patterns for each sample platform and then discussed each design pattern and its overall comparison. According to the analysis results of an individual design pattern, APP design patterns are recommended for the platforms whose quality requirements are functional applications, loading response speed, and user experience. AWD design patterns are recommended for the platforms whose quality requirements are information connectivity and interface design and layout. RWD design patterns are recommended for the platforms whose quality requirements are platform visibility and information connectivity. If an existing platform has already developed traditional web design and it’s difficult to adjust greatly, the alternative of increasing the development of M.dot is recommended.

Index Terms—responsive web design, adaptive website design, M.dot, mobile application software, quality evaluation indicators.

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Cite: Yi-Qi Chen, Sun-Jen Huang, Yu-Hsiang Chien, and I-Ting Hsiao, "Quality Assessment of Web and APP Design Patterns," International Journal of Knowledge Engineering vol. 9, no. 1, pp. 14-20, 2023.

Copyright © 2023 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).