Paper Info
Title
Characterizing and Detecting Inefficient Image Displaying Issues in Android Apps
Abstract
Mobile applications (apps for short) often need to display images. However, inefficient image displaying (IID) issues are pervasive in mobile apps, and can severely impact app performance and user experience. This paper presents an empirical study of 162 real-world IID issues collected from 243 popular open-source Android apps, validating the presence and severity of IID issues, and then sheds light on these issues’ characteristics to support future research on effective issue detection. Based on the findings of this study, we developed a static IID issue detection tool TAPIR and evaluated it with real-world Android apps. The experimental evaluations show encouraging results: TAPIR detected 43 previously-unknown IID issues in the latest version of the 243 apps, 16 of which have been confirmed by respective developers and 13 have been fixed.
Year
DOI
Venue
2019
10.1109/SANER.2019.8668030
2019 IEEE 26th International Conference on Software Analysis, Evolution and Reengineering (SANER)
Keywords
Field
DocType
Decoding,Computer bugs,Open source software,Degradation,Inspection,Keyword search
User experience design,World Wide Web,Android (operating system),Computer science,Tapir,Keyword search,Software bug,Mobile apps,Open source software,Empirical research
Conference
ISBN
Citations 
PageRank 
978-1-7281-0591-8
2
0.35
References 
Authors
0
6
Name
Order
Citations
PageRank
Wenjie Li136859.74
Yanyan Jiang26212.60
Chang Xu330214.79
Yepang Liu441524.58
Xiaoxing Ma551157.89
Jian Lü6139397.91