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User behavior pattern mining and reuse across similar Android apps
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DOI：10.1016/j.jss.2021.111085.png)
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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.
Keyword:
Android apps
Behavior pattern reuse
Semantic-based event fuzzy matching
GUI model
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5.5K
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