Random GUI testing of android application using behavioral model

Woramet Muangsiri, Shingo Takada

研究成果: Conference contribution

2 被引用数 (Scopus)

抄録

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. In this work, we propose a behavioralbased GUI testing approach for mobile applications that achieves faster and higher coverage. Our 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 is 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. We evaluated our approach on three open-source Android applications, and compared it with other approaches. Our approach showed the effectiveness of our tool.

本文言語English
ホスト出版物のタイトルProceedings - SEKE 2017
ホスト出版物のサブタイトル29th International Conference on Software Engineering and Knowledge Engineering
出版社Knowledge Systems Institute Graduate School
ページ266-271
ページ数6
ISBN(電子版)1891706411
DOI
出版ステータスPublished - 2017
イベント29th International Conference on Software Engineering and Knowledge Engineering, SEKE 2017 - Pittsburgh, United States
継続期間: 2017 7 52017 7 7

出版物シリーズ

名前Proceedings of the International Conference on Software Engineering and Knowledge Engineering, SEKE
ISSN(印刷版)2325-9000
ISSN(電子版)2325-9086

Other

Other29th International Conference on Software Engineering and Knowledge Engineering, SEKE 2017
CountryUnited States
CityPittsburgh
Period17/7/517/7/7

ASJC Scopus subject areas

  • Software

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