Search-Based Test Generation for Android Apps

Despite their growing popularity, apps tend to contain defects which can ultimately manifest as failures (or crashes) to endusers. Different automated tools for testing Android apps have been proposed in order to improve software quality. Although Genetic Algorithms and Evolutionary Algorithms (EA)...

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Bibliographic Details
Published in:	Proceedings of the ACM/IEEE 42nd International Conference on Software Engineering: Companion Proceedings pp. 230 - 233
Main Author:	Moreno, Ivan Arcuschin
Format:	Conference Proceeding
Language:	English
Published:	ACM 01.10.2020
Subjects:	Android testing evolutionary algorithms Evolutionary computation Generators Open source software Search problems search-based Test pattern generators Testing
Online Access:	Get full text
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Summary:	Despite their growing popularity, apps tend to contain defects which can ultimately manifest as failures (or crashes) to endusers. Different automated tools for testing Android apps have been proposed in order to improve software quality. Although Genetic Algorithms and Evolutionary Algorithms (EA) have been promising in recent years, in light of recent results, it seems they are not yet fully tailored to the problem of Android test generation. Thus, this thesis aims to design and evaluate algorithms for alleviating the burden of testing Android apps. In particular, I plan to investigate which is the best search-based algorithm for this particular problem. As the thesis advances, I expect to develop a fully open-source test case generator for Android applications that will serve as a framework for comparing different algorithms. These algorithms will be compared using statistical analysis on both open-source (i.e., from F-Droid) and commercial applications (i.e., from Google Play Store).
DOI:	10.1145/3377812.3381389