Checking app behavior against app descriptions

By Alessandra Gorla, Ilaria Tavecchia, Florian Gross, Andreas Zeller. International Conference on Software Engineering, 2014

460 citations recorded by the source corpus.

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Automated Test Input Generation for Android: Are We There Yet? (E) (2015, unknown): “In fact, Android apps heavily use features, such as native code, reflection and code obfuscation, that hit the limitations of almost every static analysis tool [4], [5], [11].”
Bug report, feature request, or simply praise? On automatically classifying app reviews (2015, background): “Finally, there is a large body of knowledge on predicting defects by mining software repositories [10].”
When Machine Learning Meets Privacy (2020, background): “Understanding the privacy risks of mobile phone applications with the aid of ML have been considered in [9, 46].”
Guided GUI testing of android apps with minimal restart and approximate learning (2013, background): “Automated testing techniques can also be directly used to find crashing bugs [94, 121], responsiveness bugs [89,116], concurrency bugs [21,71], and security problems [5, 15,39,92] One may argue that test minimization might not be necessary for the future if automated testing techniques continue to i”
A Survey of App Store Analysis for Software Engineering (2017, methodology): “performed malware detection by clustering app descriptions and identifying API usage outliers [78].”