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"Silent Is Not Actually Silent": An Investigation of Toxicity on Bug Report Discussion

Mia Mohammad Imran, Jaydeb Sarker

TL;DR

This paper investigates toxicity in GitHub bug report discussions by combining dataset construction, automated toxicity detection with ToxiCR and LLaMA, and manual qualitative analysis of 203 bug threads (including 81 toxic) to identify 11 toxicity subcategories and factors driving toxicity. It reveals that toxicity often arises from perceived mismatches between bug severity and maintainer priorities, frustrations with tools, and lapses in professional communication, and that toxic threads are less likely to be resolved or linked to pull requests. The findings motivate practical recommendations such as transparent severity-priority management, enforcement of a Code of Conduct for external participants, and improved toxicity detection that accounts for domain-specific language. Collectively, the work highlights how toxicity degrades collaboration and bug resolution and lays the groundwork for automated and organizational interventions to foster healthier bug discussion dynamics in open-source projects.

Abstract

Toxicity in bug report discussions poses significant challenges to the collaborative dynamics of open-source software development. Bug reports are crucial for identifying and resolving defects, yet their inherently problem-focused nature and emotionally charged context make them susceptible to toxic interactions. This study explores toxicity in GitHub bug reports through a qualitative analysis of 203 bug threads, including 81 toxic ones. Our findings reveal that toxicity frequently arises from misaligned perceptions of bug severity and priority, unresolved frustrations with tools, and lapses in professional communication. These toxic interactions not only derail productive discussions but also reduce the likelihood of actionable outcomes, such as linking issues with pull requests. Our preliminary findings offer actionable recommendations to improve bug resolution by mitigating toxicity.

"Silent Is Not Actually Silent": An Investigation of Toxicity on Bug Report Discussion

TL;DR

This paper investigates toxicity in GitHub bug report discussions by combining dataset construction, automated toxicity detection with ToxiCR and LLaMA, and manual qualitative analysis of 203 bug threads (including 81 toxic) to identify 11 toxicity subcategories and factors driving toxicity. It reveals that toxicity often arises from perceived mismatches between bug severity and maintainer priorities, frustrations with tools, and lapses in professional communication, and that toxic threads are less likely to be resolved or linked to pull requests. The findings motivate practical recommendations such as transparent severity-priority management, enforcement of a Code of Conduct for external participants, and improved toxicity detection that accounts for domain-specific language. Collectively, the work highlights how toxicity degrades collaboration and bug resolution and lays the groundwork for automated and organizational interventions to foster healthier bug discussion dynamics in open-source projects.

Abstract

Toxicity in bug report discussions poses significant challenges to the collaborative dynamics of open-source software development. Bug reports are crucial for identifying and resolving defects, yet their inherently problem-focused nature and emotionally charged context make them susceptible to toxic interactions. This study explores toxicity in GitHub bug reports through a qualitative analysis of 203 bug threads, including 81 toxic ones. Our findings reveal that toxicity frequently arises from misaligned perceptions of bug severity and priority, unresolved frustrations with tools, and lapses in professional communication. These toxic interactions not only derail productive discussions but also reduce the likelihood of actionable outcomes, such as linking issues with pull requests. Our preliminary findings offer actionable recommendations to improve bug resolution by mitigating toxicity.

Paper Structure

This paper contains 9 sections, 1 figure, 2 tables.

Figures (1)

  • Figure 1: Toxic Interaction in Bug Report Discussion (blue marked text shows toxic phrase)