User behavior pattern mining and reuse across similar Android apps

Nowadays, Android apps have penetrated all aspects of our lives. Despite their popularity, understanding 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...

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Veröffentlicht in:The Journal of systems and software 2022-01, Vol.183, p.111085, Article 111085
Hauptverfasser: Mao, Qun, Wang, Weiwei, You, Feng, Zhao, Ruilian, Li, Zheng
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Sprache:eng
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Zusammenfassung:Nowadays, Android apps have penetrated all aspects of our lives. Despite their popularity, understanding 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. •A user behavior pattern mining and reuse approach across similar apps is proposed.•A semantic-based event fuzzy mapping strategy is raised to match events across apps.•A continuous workflow generation strategy is presented to reproduce behavior patterns to new apps.
ISSN:0164-1212
1873-1228
DOI:10.1016/j.jss.2021.111085