Random GUI Testing of Android Application Using Behavioral Model

Woramet Muangsiri, Shingo Takada

Research output: Contribution to journalArticlepeer-review

11 Citations (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.

Original languageEnglish
Pages (from-to)1603-1612
Number of pages10
JournalInternational Journal of Software Engineering and Knowledge Engineering
Issue number9-10
Publication statusPublished - 2017 Dec 1


  • GUI testing
  • Testing tools
  • android
  • behavioral model
  • testing automation

ASJC Scopus subject areas

  • Software
  • Computer Networks and Communications
  • Computer Graphics and Computer-Aided Design
  • Artificial Intelligence


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