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- W3150217209 abstract "This paper introduces app store mining and analysis as a form of software repository mining. Unlike other software repositories traditionally used in MSR work, app stores usually do not provide source code. However, they do provide a wealth of other information in the form of pricing and customer reviews. Therefore, we use data mining to extract feature information, which we then combine with more readily available information to analyse apps' technical, customer and business aspects. We applied our approach to the 32,108 non-zero priced apps available in the Blackberry app store in September 2011. Our results show that there is a strong correlation between customer rating and the rank of app downloads, though perhaps surprisingly, there is no correlation between price and downloads, nor between price and rating. More importantly, we show that these correlation findings carry over to (and are even occasionally enhanced within) the space of data mined app features, providing evidence that our `App store MSR' approach can be valuable to app developers." @default.
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- W3150217209 date "2012-06-01" @default.
- W3150217209 modified "2023-10-16" @default.
- W3150217209 title "App store mining and analysis: MSR for app stores" @default.
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- W3150217209 doi "https://doi.org/10.1109/msr.2012.6224306" @default.
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