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On the Detection of Structural Aesthetic Defects of Android Mobile User Interfaces with a Metrics-based Tool

Abstract : Smartphone users are striving for easy-to-learn and use mobile apps user interfaces. Accomplishing these qualities demands an iterative evaluation of the Mobile User Interface (MUI). Several studies stress the value of providing a MUI with a pleasing look and feel to engaging end-users. The MUI, therefore, needs to be free from all kinds of structural aesthetic defects. Such defects are indicators of poor design decisions interfering with the consistency of a MUI and making it more difficult to use. To this end, we are proposing a tool (Aesthetic Defects DEtection Tool (ADDET)) to determine the structural aesthetic dimension of MUIs. Automating this process is useful to designers in evaluating the quality of their designs. Our approach is composed of two modules. (1) Metrics assessment is based on the static analysis of a tree-structured layout of the MUI. We used 15 geometric metrics (also known as structural or aesthetic metrics) to check various structural properties before a defect is triggered. (2) Defects detection: The manual combination of metrics and defects are time-consuming and user-dependent when determining a detection rule. Thus, we perceive the process of identification of defects as an optimization problem. We aim to automatically combine the metrics related to a particular defect and optimize the accuracy of the rules created by assigning a weight, representing the metric importance in detecting a defect. We conducted a quantitative and qualitative analysis to evaluate the accuracy of the proposed tool in computing metrics and detecting defects. The findings affirm the tool’s reliability when assessing a MUI’s structural design problems with 71% accuracy.
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Submitted on : Wednesday, June 23, 2021 - 11:19:19 AM
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Narjes Bessghaier, Makram Soui, Christophe Kolski, Mabrouka Chouchane. On the Detection of Structural Aesthetic Defects of Android Mobile User Interfaces with a Metrics-based Tool. ACM Transactions on Interactive Intelligent Systems , Association for Computing Machinery (ACM), 2021, 11 (1), pp.1-27. ⟨10.1145/3410468⟩. ⟨hal-03268483⟩



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