Understanding the characteristics and the role of visual issue reports

Issue reports are a pivotal interface between developers and users for receiving information about bugs in their products. In practice, reproducing those bugs is challenging, since issue reports often contain incorrect information or lack sufficient information. Furthermore, the poor quality of issu...

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Veröffentlicht in:Empirical software engineering : an international journal 2024-07, Vol.29 (4), p.89, Article 89
Hauptverfasser: Kuramoto, Hiroki, Wang, Dong, Kondo, Masanari, Kashiwa, Yutaro, Kamei, Yasutaka, Ubayashi, Naoyasu
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Sprache:eng
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Zusammenfassung:Issue reports are a pivotal interface between developers and users for receiving information about bugs in their products. In practice, reproducing those bugs is challenging, since issue reports often contain incorrect information or lack sufficient information. Furthermore, the poor quality of issue reports would have the effect of delaying the entire bug-fixing process. To enhance bug comprehension and facilitate bug reproduction, GitHub Issue allows users to embed visuals such as images and videos to complement the textual description. Hence, we conduct an empirical study on 34 active GitHub repositories to quantitatively analyze the difference between visual issue reports and non-visual ones, and qualitatively analyze the characteristics of visuals and the usage of visuals in bug types. Our results show that visual issue reports have a significantly higher probability of reporting bugs. Visual reports also tend to receive the first comment and complete the conversation in a relatively shorter time. Visuals are frequently used to present the program behavior and the user interface, with the major purpose of introducing problems in reports. Additionally, we observe that visuals are commonly used to report GUI-related bugs, but they are rarely used to report configuration bugs in comparison to non-visual issue reports. To summarize, our work highlights the role of visual play in the bug-fixing process and lays the foundation for future research to support bug comprehension by exploiting visuals.
ISSN:1382-3256
1573-7616
DOI:10.1007/s10664-024-10459-3