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Supporting Developers in Addressing Human-Centric Issues in Mobile Apps

delete2023-04-01
delete6
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OA
AI
H
Hourieh Khalajzadeh *
M
Mojtaba Shahin
H
Humphrey O. Obie
P
Pragya Agrawal
J
John Grundy
DOI:10.1109/TSE.2022.3212329delete
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摘要

摘要

En 中文
Failure to consider the characteristics, limitations, and abilities of diverse end-users during mobile app development may lead to problems for end-users, such as accessibility and usability issues. We refer to this class of problems as human-centric issues. Despite their importance, there is a limited understanding of the types of human-centric issues that are encountered by end-users and taken into account by the developers of mobile apps. In this paper, we examine what human-centric issues end-users report through Google App Store reviews, what human-centric issues are a topic of discussion for developers on GitHub, and whether end-users and developers discuss the same human-centric issues. We then investigate whether an automated tool might help detect such human-centric issues and whether developers would find such a tool useful. To do this, we conducted an empirical study by extracting and manually analysing a random sample of 1,200 app reviews and 1,200 issue comments from 12 diverse projects that exist on both Google App Store and GitHub. Our analysis led to a taxonomy of human-centric issues that characterises human-centric issues into three-high level categories: App Usage, Inclusiveness, and User Reaction. We then developed machine learning and deep learning models that are promising in automatically identifying and classifying human-centric issues from app reviews and developer discussions. A survey of mobile app developers shows that the automated detection of human-centric issues has practical applications. Guided by our findings, we highlight some implications and possible future work to further understand and better incorporate addressing human-centric issues into mobile app development.
Keyword:
Mobile applications
Software development management
Internet
Taxonomy
Software systems
Australia
Security
Human-centric issues
GitHub repositories
Google Play Store
human aspects
machine learning
deep learning

期刊

IEEE Transactions on Software Engineering 封面图
IEEE Transactions on Software Engineering
IF:
5.6
论文数:
2.9K
被引数:
1.1W

机构

M
Monash University
学者数:
5.4W
论文数: 5.4W
被引数: 79
D
Deakin University
学者数:
2.0W
论文数: 2.1W
被引数: 2.8W
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