A Grey-Box Approach for Automated GUI-Model Generation of Mobile Applications

By Wei Yang, Mukul R. Prasad, Tao Xie. Fundamental Approaches to Software Engineering, 2013

330 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Information Systems

View Paper: https://www.semanticscholar.org/paper/101785b37e791331e254849269e906c39f6c4500

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Koushik Sen
2. Mark Harman
3. Yue Jia
4. Yuting Chen
5. Sam Malek
6. Ke Mao
7. Philippe B Kruchten
8. Andreas Zeller

In Information Systems

1. Koushik Sen
2. Yves Le Traon
3. Mike Papadakis
4. George C. Necula
5. Wontae Choi
6. Yue Jia
7. Zhendong Su
8. Mark Harman

Citations in the corpus

• Sapienz: multi-objective automated testing for Android applications (2016, methodology): “ORBIT [61] is based on a combination of dynamic GUI crawling and static code analysis, using analysis to avoid generation of irrelevant UI events.”
• Static analysis of android apps: A systematic literature review (2017, methodology): “WALA IR A3E [57], AAPL [61], AnDarwin [49], AndroidLeaks [80], AsDroid [95], Asynchronizer [144], CHEX [8], DNADroid [48], Hopper [79], ORBIT [154], Poeplau et al.”
• Checking app behavior against app descriptions (2014, methodology): “Integrating such techniques in CHABADA , combined with automated test generation [12, 27, 15, 1], would allow to learn normal and abnormal patterns of information flow; this is part of our future work (Section 6).”
• Guided GUI testing of android apps with minimal restart and approximate learning (2013, methodology): “[45] take online model-based testing approach similar to Crawljax [29].”
• Real Challenges in Mobile App Development (2013, background): “Similarly, others [37], [38] are looking into Android apps.”
• Automated Test Input Generation for Android: Are We There Yet? (E) (2015, neutral): “Among the rest of the tools, we had to exclude also EvoDroid and ORBIT.”
• Guided, stochastic model-based GUI testing of Android apps (2017, methodology): “Despite much effort [1, 2, 19, 42, 57, 67] in manually or automatically constructing models to represent GUI interactions, MBT’s effectiveness is still limited due to incomplete UI exploration.”
• EvoDroid: segmented evolutionary testing of Android apps (2014, methodology): “Yang et al. [38] described a grey-box model creation technique that similar to our work is concerned with deriving models for testing of Android app and can potentially be substitued for our models.”