Random GUI Testing of Android Application Using Behavioral Model

Woramet Muangsiri, Shingo Takada

研究成果: Article査読

5 被引用数 (Scopus)


Automated GUI testing based on behavioral model is one of the most efficient testing approaches. By mining user usage, test scenarios can be generated based on statistical models such as Markov chain. However, these works require static analysis before starting the exploration which requires too much prerequisites and time. To address these challenges, we propose a behavioral-based GUI testing approach for mobile applications that achieves faster and higher coverage. The proposed approach does not conduct static analysis. It creates a behavioral model from usage logs by applying a statistical model. The events within the behavioral model are mapped to GUI components in a GUI tree. Finally, it updates the model dynamically to increase the probability of an event that rarely or never occurs when users use the application. The proposed approach was evaluated on four open-source Android applications, and compared with the state-of-the-art tools and manual testing. The main evaluation criteria are code coverage and ability to find errors. The proposed approach performed better than the current state-of-the-art automated testing tools in most aspects.

ジャーナルInternational Journal of Software Engineering and Knowledge Engineering
出版ステータスPublished - 2017 12 1

ASJC Scopus subject areas

  • ソフトウェア
  • コンピュータ ネットワークおよび通信
  • コンピュータ グラフィックスおよびコンピュータ支援設計
  • 人工知能


「Random GUI Testing of Android Application Using Behavioral Model」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。