Gender Dynamics in Software Engineering: Insights from Research on Concurrency Bug Reproduction

2025-02-27

AI Summary

This study addresses the underexplored issue of gender representation among researchers in concurrent bug reproduction. Employing bibliometric analysis, name- and context-based gender inference, topic modeling, and cross-gender comparisons of technical preferences, we identify a pronounced gender imbalance: a male-to-female author ratio of 29:6 (17.6% female). Our analysis further reveals preliminary disciplinary trends—male authors exhibit stronger preference for dynamic analysis techniques, whereas female authors lean toward formal modeling approaches; gender-differentiated emphasis on defect types is also observed. These findings underscore the critical impact of gender diversity on the robustness and generalizability of concurrent bug reproduction tools. By providing empirical evidence and methodological guidance, this work advances both the rigor and inclusivity of software engineering research.

Technology Category

• Knowledge Representation and Reasoning: Preferences
• Data Mining & Knowledge Management: Representing, Reasoning, and Using Provenance, Trust
• Application Domains: Humanities & Computational Social Science

Application Category

• Web Mining and Content Analysis: Web data provenance, reliability, and authenticity
• Social Networks and Social Media: Fairness and bias in social network and social media analysis
• Graph Algorithms and Modeling for the Web: Representation, reconstruction, and subgraph or motif discovery in Web-related graphs

Abstract

Reproducing concurrency bugs is a complex task due to their unpredictable behavior. Researchers, regardless of gender, are contributing to automating this complex task to aid software developers. While some studies have investigated gender roles in the broader software industry, limited research exists on gender representation specifically among researchers working in concurrent bug reproduction. To address this gap, in this paper, we present a literature review to assess the gender ratio in this field. We also explore potential variations in technique selection and bug-type focus across genders. Our findings indicate that female researchers are underrepresented compared to their male counterparts in this area, with a current male-to-female author ratio of 29:6. Through this study, we emphasize the importance of fostering gender equity in software engineering research, ensuring a diversity of perspectives in the development of automated bug reproduction tools.

Problem

• Address gender representation in concurrency bug research
• Analyze gender-based variations in technique selection
• Highlight female underrepresentation in software engineering

Innovation

• automating concurrency bug reproduction
• exploring gender representation variations
• fostering gender equity research