ComboDroid: generating high-quality test inputs for Android apps via use case combinations

Abstract

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 white-box human testing expert.

Jue Wang

Ph.D.

My research interests include program analisys, program testing, and Android app quality assurance.