Name
Abstract | ||
|---|---|---|
Facing the limited resource of smartphones, asynchronous programming significantly improves the performance of Android applications. Android provides several packaged components to ease the development of asynchronous programming. Among them, the AsyncTask component is widely used by developers since it is easy to implement. However, the abuse of AsyncTask component can decrease responsiveness and even lead to crashes. By investigating the Android Developer Documentation and technical forums, we summarize five misuse patterns about AsyncTask. To detect them, we propose a flow, context, object and field-sensitive inter-procedural static analysis approach. Specifically, the static analysis includes typestate analysis, reference analysis and loop analysis. Based on the AsyncTask-related information obtained during static analysis, we check the misuse according to predefined detection rules. The proposed approach is implemented into a tool called AsyncChecker. We evaluate AsyncChecker on a self-designed benchmark suite called AsyncBench and 1,759 real-world apps. AsyncChecker finds 17,946 misused AsyncTask instances in 1,417 real-world apps (80.6%). The precision, recall and F-measure of AsyncChecker on real-world applications are 97.2%, 89.8% and 0.93, respectively. Compared with existing tools, AsyncChecker can detect more asynchronous problems. We report the misuse problems to developers via GitHub. Several developers have confirmed and fixed the problems found by AsyncChecker. The result implies that our approach is effective and developers do take the misuse of AsyncTask as a serious problem.
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Year | DOI | Venue |
|---|---|---|
2020 | 10.1145/3368089.3409699 | ESEC/FSE '20: 28th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering
Virtual Event
USA
November, 2020 |
DocType | ISBN | Citations |
Conference | 978-1-4503-7043-1 | 0 |
PageRank | References | Authors |
0.34 | 0 | 7 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Linjie Pan | 1 | 5 | 1.75 |
| Baoquan Cui | 2 | 0 | 0.34 |
| Hao Liu | 3 | 24 | 2.68 |
| Jiwei Yan | 4 | 10 | 4.22 |
| Siqi Wang | 5 | 0 | 0.34 |
| Jun Yan | 6 | 248 | 21.97 |
| Jian Zhang | 7 | 32 | 12.20 |