Which Version Should Be Released to App Store?

Abstract

Background: Several mobile app releases do not find their way to the end users. Our analysis of 11,514 releases across 917 open source mobile apps revealed that 44.3% of releases created in GitHub never shipped to the app store (market). Aims: We introduce "marketability" of open source mobile apps as a new release decision problem. Considering app stores as a complex system with unknown treatments, we evaluate performance of predictive models and analogical reasoning for marketability decisions. Method: We performed a survey with 22 release engineers to identify the importance of marketability release decision. We compared different classifiers to predict release marketability. For guiding the transition of not successfully marketable releases into successful ones, we used analogical reasoning. We evaluated our results both internally (over time) and externally (by developers). Results: Random forest classification performed best with F1 score of 78%. Analyzing 58 releases over time showed that, for 81% of them, analogical reasoning could correctly identify changes in the majority of release attributes. A survey with seven developers showed the usefulness of our method for supporting real world decisions. Conclusions: Marketability decisions of mobile apps can be supported by using predictive analytics and by considering and adopting similar experience from the past.