User behavior pattern mining and reuse across similar Android apps

被引:6
|
作者
Mao, Qun [1 ]
Wang, Weiwei [1 ]
You, Feng [1 ]
Zhao, Ruilian [1 ]
Li, Zheng [1 ]
机构
[1] Beijing Univ Chem Technol, Coll Informat Sci & Technol, Beijing 100029, Peoples R China
基金
中国国家自然科学基金;
关键词
Android apps; Behavior pattern reuse; Semantic-based event fuzzy matching; GUI model;
D O I
10.1016/j.jss.2021.111085
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Nowadays, Android apps have penetrated all aspects of our lives. Despite their popularity, understand-ing their behaviors is still a challenging task. Considering that many Android apps are in the same category and share similar workflows, in this paper, we propose a user behavior pattern mining and reuse approach across similar Android apps, thereby reducing the cost of understanding new apps. Particularly, for a specific new app, to figure out its typical behaviors, the behavior patterns that refer to the frequently-occurring workflows can be obtained from another similar app and transferred to this app. Moreover, to reuse the behavior patterns on this app, a semantic-based event fuzzy matching strategy and continuous workflow generation strategy are raised to generate workflows for this app. To evaluate our approach's effectiveness and rationality, we conduct a series of experiments on 25 Android apps in five categories. Furthermore, the experimental results show that 88.3% of behavior patterns can be completely reused on similar apps, and the generated workflows cover 89.1% of the top 20% of important states. (c) 2021 Elsevier Inc. All rights reserved.
引用
收藏
页数:14
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