ComboDroid: Generating High-Quality Test Inputs for Android Apps via Use Case Combinations
Android apps demand high-quality test inputs, whose generation remains an open challenge. Existing techniques fall short on exploring complex app functionalities reachable only by a long, meaningful, and effective test input. Observing that such test inputs can usually be decomposed into relatively independent short use cases, this paper presents ComboDroid, a fundamentally different Android app testing framework. ComboDroid obtains use cases for manifesting a specific app functionality (either manually provided or automatically extracted), and systematically enumerates the combinations of use cases, yielding high-quality test inputs.
The evaluation results of ComboDroid on real-world apps are encouraging. Our fully automatic variant outperformed the best existing technique APE by covering 4.6% more code (APE only outperformed Monkey by 2.1%), and revealed four previously unknown bugs in extensively tested subjects. Our semi-automatic variant boosts the manual use cases obtained with little manual labor, achieving a comparable coverage (only 3.2% less) with a human testing expert.
Mon 5 Oct (GMT+09:00) Seoul change
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Jiwei YanInstitute of Software, Chinese Academy of Sciences, Hao LiuBeijing University of Technology, Linjie PanInstitute of Software, Chinese Academy of Sciences, Jun YanInstitute of Software, Chinese Academy of Sciences, Jian ZhangInstitute of Software, Chinese Academy of Sciences, Bin LiangRenmin University of China, China
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