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.
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Carlos Bernal-CárdenasWilliam and Mary, Nathan CooperCollege of William & Mary, Kevin MoranWilliam & Mary/George Mason University, Oscar ChaparroCollege of William & Mary, Andrian MarcusUniversity of Texas at Dallas, Denys PoshyvanykWilliam and MaryPre-print Media Attached
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Gian Luca ScocciaUniversity of L'Aquila, Ivano Malavolta, Marco AutiliUniversity of L'Aquila, Italy, Amleto Di SalleUniversity of L'Aquila, Paola InverardiUniversity of L'AquilaLink to publication DOI Pre-print
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