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Erschienen in: Empirical Software Engineering 7/2022

01.12.2022

Using Screenshot Attachments in Issue Reports for Triaging

verfasst von: Ethem Utku Aktas, Cemal Yilmaz

Erschienen in: Empirical Software Engineering | Ausgabe 7/2022

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Abstract

In previous work, we deployed IssueTAG, which uses the one-line summary and the description fields of the issue reports to automatically assign them to the stakeholders, who are responsible for resolving the reported issues. Since its deployment on January 12, 2018 at Softtech – the software subsidiary of the largest private bank in Turkey, IssueTAG has made a total of 301,752 assignments (as of November 2021). One observation we make is that a large fraction of the issue reports submitted to Softtech has screenshot attachments and, in the presence of such attachments, the reports often convey less information in their one-line summary and the description fields, which tends to reduce the assignment accuracy. In this work, we use the screenshot attachments as an additional source of information to further improve the assignment accuracy, which, to the best of our knowledge, has not been studied before for automatic issue assignments. In particular, we develop a number of multi-source assignment models, which use both the issue reports and the screenshot attachments, as well as a number of single source models, which use either the issue reports or the screenshot attachments, and empirically evaluate them on real issue reports. Compared to the currently deployed single-source model in the field, the best multi-source model improved the assignment accuracy from 0.848 to 0.855 at an acceptable overhead cost, reducing the overall 3.3 percentage-point deficit between the human triagers and the deployed system by 0.7 points.

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Metadaten
Titel
Using Screenshot Attachments in Issue Reports for Triaging
verfasst von
Ethem Utku Aktas
Cemal Yilmaz
Publikationsdatum
01.12.2022
Verlag
Springer US
Erschienen in
Empirical Software Engineering / Ausgabe 7/2022
Print ISSN: 1382-3256
Elektronische ISSN: 1573-7616
DOI
https://doi.org/10.1007/s10664-022-10228-0

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