Efficient exploration of hard-to-find function in GUIs: A method and best practice

Abstract

With the proliferation of mobile applications (apps), there has been a noticeable trend towards diversification in app functionalities to cater to evolving user needs and preferences. This evolution is evident in ongoing efforts towards app feature recommendation, reflecting a concerted endeavor to enhance user experience and satisfaction. However, the increasing complexity in app functionalities, particularly within the Graphical User Interface (GUI), presents significant challenges for users to find their desired functions. Further, by conducting an online survey, we found that 85% of participants encounter difficulties in locating desired functionalities within apps, which can lead to frustration and even app abandonment. To tackle this challenge, we propose an approach that leverages GUI screenshots and layout files to analyze app functions. Our approach involves vectorizing app functions based on user search times and function descriptions, followed by personalized analysis, initial difficulty assessment, and refinement through clustering techniques. To evaluate our method, we carry out experiments on 49 apps across 8 categories demonstrate the effectiveness of our approach. Our approach achieves an accuracy rate of 91.29% on average in identifying hard-to-find functions and observes significant performance improvements after reducing random data. Feedback from developers further confirms the practical utility of our approach in crafting user-friendly GUIs and minimizing the risk of crucial functions being overlooked.