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Empirical Software Engineering

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25.06.2019

An empirical study on quality of Android applications written in Kotlin language

Erschienen in: Empirical Software Engineering | Ausgabe 6/2019

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Abstract

Context

During the last years, developers of mobile applications have the possibility to use new paradigms and tools for developing mobile applications. For instance, since 2017, Android developers have the official support to write Android applications using Kotlin language. Kotlin is programming language fully interoperable with Java that combines object-oriented and functional features.

Objective

The goal of this paper is twofold. First, it aims to study the degree of adoption of Kotlin language on the development of open-source Android applications and to measure the amount of Kotlin code inside those applications. Secondly, it aims to measure the quality of Android applications that are written using Kotlin and to compare it with the quality of Android applications written using Java.

Method

We first defined a method to detect Kotlin applications from a dataset of open-source Android applications. Then, we analyzed those applications to detect instances of code smells and computed an estimation of the quality of the applications. Finally, we studied how the introduction of Kotlin code impacts on the quality of an Android application.

Results

Our experiment found that 11.26% of applications from a dataset with 2,167 open-source applications have been written (partially or fully) using Kotlin language. We found that the introduction of Kotlin code increases the quality, in terms of the presence of 10 different code smells studied, 4 object-oriented and 6 Android, of the majority of the Android applications initially written in Java.

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https://developer.android.com/about/

https://play.google.com

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https://www.xamarin.com

https://facebook.github.io/react-native

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Last visit: 06/04/2018.

https://cloud.google.com/bigquery/public-data/github

Last visit: 16/10/2018.

Experiment executed the June 4th, 2018.

AndroidTimeMachine resources: https://androidtimemachine.github.io/dataset/ and https://github.com/AndroidTimeMachine/open_source_android_apps

https://github.com/UPHF/kotlinandroid/blob/master/docs/multiple_manifest_problem.md.

In the appendix we list that applications that suffer the mentioned problem: https://github.com/UPHF/kotlinandroid/blob/master/docs/wrong_match.md.

FAMAZOA dataset: https://github.com/UPHF/kotlinandroid/blob/master/docs/final_dataset.md

http://cloc.sourceforge.net/

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Version of Paprika used: commit 5ebd34 https://github.com/GeoffreyHecht/paprika/commit/5ebd349ed3067914386e8c6a05e87ff161f9edd1

https://developer.android.com/about/dashboards/ Last visit: 06/11/2018

Hecht (2016a) considers that a method is “long” (LM) if it has more than 17 instructions.

Applications classified as Kotlin: https://github.com/UPHF/kotlinandroid/blob/master/docs/final_kotlin_dataset.md

Classification of the evolution trends. https://github.com/UPHF/kotlinandroid/tree/master/docs/evolution

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Titel: An empirical study on quality of Android applications written in Kotlin language
Publikationsdatum: 25.06.2019
Erschienen in: Empirical Software Engineering / Ausgabe 6/2019
Print ISSN: 1382-3256
Elektronische ISSN: 1573-7616
DOI: https://doi.org/10.1007/s10664-019-09727-4

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Abstract

Context

Objective

Method

Results

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