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In an experimental evaluation conducted on real-world Android apps, amplified test cases produced by Prefest from automatically generated test cases covered significantly more code of the apps and detected 7 real bugs, and the tool’s test amplification time was at the same order of magnitude as the running time of the input test cases. Given an Android app and a set of test cases for the app, Prefest amplifies the test cases with a small number of configurations to exercise more behaviors and detect more bugs that are related to preferences. This paper presents the Prefest approach to effective testing of Android apps with preferences. Unfortunately, few test cases explicitly specify the assignments of valid values to the preferences, or configurations, under which they should be executed, and few existing mobile testing tools take the impact of preferences into account or provide help to testers in identifying and setting up the configurations for running the tests. Preferences allow users to change app features and behaviors dynamically, and therefore their impacts need to be considered when testing the apps. Preferences, the setting options provided by Android, are an essential part of Android apps. Nonetheless, the feedback received indicates that the synthesized Espresso tests are still useful for projects with few or no test cases, serving as a starting point for creating new ones. It also points out that further research is needed to find ways to improve the testability of Android apps either manually or automatically. This problem is aggravated in some cases by the incomplete or ambiguous definition of GUI components and layouts. Our empirical study shows that the creation of Espresso tests is difficult, mostly due to the lack of unique properties to unambiguously identify specific widgets in the UI. We also include feedback from developers of open-source projects and an industrial app. The prototype is then evaluated on 12 open-source Android apps, followed by an analysis and discussion of challenges and limitations. The original Super Metroid on the SNES came out in 1994 to enthrall audiences with its level design and explorative game design.
We build on top of the MATE testing tool and implement a prototype that enables this study. In this work we present an empirical study on the challenges of automatically synthesizing Espresso test suites from sequences of interactions over widgets.
This hinders the ability of developers to add those tests to their existing test suites, or adapt them to new scenarios- common practices in modern software development where tests are maintained and evolve alongside production code. While useful for crash reproduction and bug-fixing, these tools usually do not present the generated interactions in a format that motivates developers to read and modify such tests later on. Several tools have been proposed to automatically test Android applications, achieving outstanding results in terms of both code coverage and crash discovery.