Multiple-entry testing of Android applications by constructing activity launching contexts
Jiwei Yan, Hao Liu, Linjie Pan, Jun Yan, Jian Zhang, Bin Liang
Abstract
Existing GUI testing approaches of Android apps usually test apps from a single entry. In this way, the marginal activities far away from the default entry are difficult to be covered. The marginal activities may fail to be launched due to requiring a great number of activity transitions or involving complex user operations, leading to uneven coverage on activity components. Besides, since the test space of GUI programs is infinite, it is difficult to test activities under complete launching contexts using single-entry testing approaches. In this paper, we address these issues by constructing activity launching contexts and proposing a multiple-entry testing framework. We perform an inter-procedural, flow-, context-and pathsensitive analysis to build activity launching models and generate complete launching contexts. By activity exposing and static analysis, we could launch activities directly under various contexts without performing long event sequence on GUI. Besides, to achieve an in-depth exploration, we design an adaptive exploration framework which supports the multiple-entry exploration and dynamically assigns weights to entries in each turn.
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