The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Using GUI ripping for automated testing of Android applications
Abstract
We present AndroidRipper, an automated technique that tests Android apps via their Graphical User Interface (GUI). AndroidRipper is based on a user-interface driven ripper that automatically explores the app’s GUI with the aim of exercising the application in a structured manner. We evaluate AndroidRipper on an open-source Android app. Our results show that our GUI-based test cases are able to detect severe, previously unknown, faults in the underlying code, and the structured exploration outperforms a random approach.
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Citations
Cites
GUI ripping: reverse engineering of graphical user interfaces for testing
Memon, A., Banerjee, I., & Nagarajan, A. (2004) · 10th Working Conference on Reverse Engineering, 2003. WCRE 2003. Proceedings. · doi:10.1109/wcre.2003.1287256 · Cited by 379
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Link Prediction for Completing Graphical Software Models Using Neural Networks
Leblebici, O., Tuglular, T., & Belli, F. (2023) · IEEE Access · doi:10.1109/access.2023.3323591 · Cited by 1
Metadata
- Authors
- Amalfitano, D., Fasolino, A. R., Tramontana, P., De Carmine, S., & Memon, A. M.
- Venue
- Proceedings of the 27th IEEE/ACM International Conference on Automated Software Engineering
- Publisher
- ACM
- Published
- 2012-09-03
- Pages
- 258-261
- OpenAlex
- W2088749975
- Cited by
- 514
- References
- 1
- FWCI
- 28.10
- Type
- conference paper
- Language
- en
- Open access
- closed
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- The paper
- Amalfitano, D., Fasolino, A. R., Tramontana, P., De Carmine, S., & Memon, A. M. (2012). Using GUI ripping for automated testing of Android applications. Proceedings of the 27th IEEE/ACM International Conference on Automated Software Engineering. https://doi.org/10.1145/2351676.2351717
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
