TY - GEN
T1 - Diversity and Inclusion in Open Source Software (OSS) Projects
T2 - 13th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, ESEM 2019
AU - Bosu, Amiangshu
AU - Sultana, Kazi Zakia
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/9
Y1 - 2019/9
N2 - Background: As the area of computing has thrived over the years, the participation of women in computing declined. Currently women represent less than 24% of the computing workforce and that number is declining. On the other hand, the ratios of women in Open Source Software (OSS) projects are even lower.Aims: The primary objective of this study is to determine the level of gender diversity among popular OSS projects and identify the presence of gender biases that may discourage females' participation.Method: On this goal, we mined the code review repositories of ten popular OSS projects. We used a semi-automated approach followed by a manual validation to identify the genders of the active contributors.Results: Our results suggest that lack of gender diversity remains an ongoing issue among all the ten projects as each of the projects had less than 10% female developers. However, many of the projects also suffer from lack of inclusion of females to leadership positions. Although none of the projects suggest significant differences between male and female developers in terms of productivity based on three different measures, data from three out of the ten projects indicate technical biases against female developers with lower code acceptance rates as well as delayed feedback during code reviews. However, biases against females are not universal as majority of the projects do not discriminate against females. The two projects with the least ratios of female contributors as core developers showed the most biases against females.Conclusion: Based on our findings, we conclude that promoting and mentoring females to leadership positions may be an effective solution to foster gender diversity.
AB - Background: As the area of computing has thrived over the years, the participation of women in computing declined. Currently women represent less than 24% of the computing workforce and that number is declining. On the other hand, the ratios of women in Open Source Software (OSS) projects are even lower.Aims: The primary objective of this study is to determine the level of gender diversity among popular OSS projects and identify the presence of gender biases that may discourage females' participation.Method: On this goal, we mined the code review repositories of ten popular OSS projects. We used a semi-automated approach followed by a manual validation to identify the genders of the active contributors.Results: Our results suggest that lack of gender diversity remains an ongoing issue among all the ten projects as each of the projects had less than 10% female developers. However, many of the projects also suffer from lack of inclusion of females to leadership positions. Although none of the projects suggest significant differences between male and female developers in terms of productivity based on three different measures, data from three out of the ten projects indicate technical biases against female developers with lower code acceptance rates as well as delayed feedback during code reviews. However, biases against females are not universal as majority of the projects do not discriminate against females. The two projects with the least ratios of female contributors as core developers showed the most biases against females.Conclusion: Based on our findings, we conclude that promoting and mentoring females to leadership positions may be an effective solution to foster gender diversity.
KW - discrimination
KW - diversity
KW - gender issues
KW - inclusion
KW - open source projects
UR - http://www.scopus.com/inward/record.url?scp=85074278900&partnerID=8YFLogxK
U2 - 10.1109/ESEM.2019.8870179
DO - 10.1109/ESEM.2019.8870179
M3 - Conference contribution
AN - SCOPUS:85074278900
T3 - International Symposium on Empirical Software Engineering and Measurement
BT - Proceedings - 13th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, ESEM 2019
PB - IEEE Computer Society
Y2 - 19 September 2019 through 20 September 2019
ER -