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.
A recent publication by Harman et al. REF discusses another form of software repository mining, which they call the "App Store Repository Mining".
App store mining and analysis: MSR for app stores
2012 9th IEEE Working Conference on Mining Software Repositories (MSR)
2012 9th IEEE Working Conference on Mining Software Repositories (MSR)
Computer Science