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Empirical Software Engineering
Erschienen in: Empirical Software Engineering 4/2019

29.01.2019

Towards prioritizing user-related issue reports of mobile applications

verfasst von: Ehsan Noei, Feng Zhang, Shaohua Wang, Ying Zou

Erschienen in: Empirical Software Engineering | Ausgabe 4/2019

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Abstract

The competitive market of mobile applications (apps) has driven app developers to pay more attention to addressing the issues of mobile apps. Prior studies have shown that addressing the issues that are reported in user-reviews shares a statistically significant relationship with star-ratings. However, despite the prevalence and importance of user-reviews and issue reports prioritization, no prior research has analyzed the relationship between issue reports prioritization and star-ratings. In this paper, we integrate user-reviews into the process of issue reports prioritization. We propose an approach to map issue reports that are recorded in issue tracking systems to user-reviews. Through an empirical study of 326 open-source Android apps, our approach achieves a precision of 79% in matching user-reviews with issue reports. Moreover, we observe that prioritizing the issue reports that are related to user-reviews shares a significant positive relationship with star-ratings. Furthermore, we use the top apps, in terms of star-ratings, to train a model for prioritizing issue reports. It is a good practice to learn from the top apps as there is no well-established approach for prioritizing issue reports. The results show that mobile apps with a similar prioritization approach to our trained model achieve higher star-ratings.
Vorheriger Artikel The impact of feature reduction techniques on defect prediction models
Nächster Artikel Gender differences in participation and reward on Stack Overflow

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Metadaten
Titel
Towards prioritizing user-related issue reports of mobile applications
verfasst von
Ehsan Noei
Feng Zhang
Shaohua Wang
Ying Zou
Publikationsdatum
29.01.2019
Verlag
Springer US
Erschienen in
Empirical Software Engineering / Ausgabe 4/2019
Print ISSN: 1382-3256
Elektronische ISSN: 1573-7616
DOI
https://doi.org/10.1007/s10664-019-09684-y

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