Self-reported activities of Android developers
Pascarella,Luca Geiger,Franz-Xaver Palomba,Fabio Di Nucci,Dario Malavolta,Ivano Bacchelli,Alberto
Pascarella,Luca
Geiger,Franz-Xaver
Palomba,Fabio
Di Nucci,Dario
Malavolta,Ivano
Bacchelli,Alberto
Abstract
To gain a deeper empirical understanding of how developers work on Android apps, we investigate self-reported activities of Android developers and to what extent these activities can be classified with machine learning techniques. To this aim, we firstly create a taxonomy of self-reported activities coming from the manual analysis of 5,000 commit messages from 8,280 Android apps. Then, we study the frequency of each category of self-reported activities identified in the taxonomy, and investigate the feasibility of an automated classification approach. Our findings can inform be used by both practitioners and researchers to take informed decisions or support other software engineering activities.
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Date
2018
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Research Projects
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Citation
Pascarella, L, Geiger, F-X, Palomba, F, Di Nucci, D, Malavolta, I & Bacchelli, A 2018, Self-reported activities of Android developers. in Proceedings - International Conference on Software Engineering. https://doi.org/10.1145/3197231.3197251
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info:eu-repo/semantics/restrictedAccess