A Graph-based Dataset of Commit History of Real-World Android apps

Conference Paper (2018)
Author(s)

Franz-Xaver Geiger (Vrije Universiteit Amsterdam)

Ivano Malavolta (Vrije Universiteit Amsterdam)

Luca Pascarella (TU Delft - Software Engineering)

Fabio Palomba (Universitat Zurich)

Dario Di Nucci (Vrije Universiteit Brussel)

A Bacchelli (Universitat Zurich)

Research Group
Software Engineering
Copyright
© 2018 Franz-Xaver Geiger, Ivano Malavolta, L. Pascarella, F. Palomba, D. Di Nucci, A. Bacchelli
More Info
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Publication Year
2018
Language
English
Copyright
© 2018 Franz-Xaver Geiger, Ivano Malavolta, L. Pascarella, F. Palomba, D. Di Nucci, A. Bacchelli
Research Group
Software Engineering
Pages (from-to)
30-33
ISBN (print)
978-1-4503-5716-6
Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Abstract

Obtaining a good dataset to conduct empirical studies on the engineering of Android apps is an open challenge. To start tackling this challenge, we present AndroidTimeMachine, the first, self-contained, publicly available dataset weaving spread-out data sources about real-world, open-source Android apps. Encoded as a graph-based database, AndroidTimeMachine concerns 8,431 real open-source Android apps and contains: (i) metadata about the apps' GitHub projects, (ii) Git repositories with full commit history and (iii) metadata extracted from the Google Play store, such as app ratings and permissions.

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