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- W2895555718 abstract "Background: An Android smartphone is an ecosystem of applications, drivers, operating system components, and assets. The volume of the software is large and the number of test cases needed to cover the functionality of an Android system is substantial. Enormous effort has been already taken to properly quantify what features and apps were tested and verified?. This insight is provided by dashboards that summarize test coverage and results per feature. One method to achieve this is to manually tag or label test cases with the topic or function they cover, much like function points. At the studied Android smartphone vendor, tests are labelled with manually defined tags, so-called feature labels (FLs), and the FLs serve to categorize 100s to 1000s test cases into 10 to 50 groups." @default.
- W2895555718 created "2018-10-12" @default.
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- W2895555718 date "2018-10-11" @default.
- W2895555718 modified "2023-10-16" @default.
- W2895555718 title "Automatic topic classification of test cases using text mining at an Android smartphone vendor" @default.
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- W2895555718 doi "https://doi.org/10.1145/3239235.3268927" @default.
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