Bridging the Gap: A Data-Driven Analysis of How Traditional Software Engineering Productivity Metrics Overlook Women’s Performance
Abstract
Traditional productivity metrics in software engineering, such as lines of code, commits, and task duration, often fail to capture essential subjective factors like collaboration and well-being. This gap disproportionately affects women, who face additional challenges including gender bias, microaggressions, and double workload. Based on a survey with 85 female software engineers in Brazil, this study analyzes how these challenges impact performance and reveals that conventional metrics undervalue women’s contributions. The findings highlight the need for a more inclusive framework that recognizes both technical and non-technical work.References
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for Women & Information Technology (NCWIT), N. C. (2023). Women in tech: 2023 update on representation.
Ford, D., Smith, J., Guo, P. J., and Parnin, C. (2017). Paradise unplugged: Identifying barriers for remote software development. In CHI Conference on Human Factors in Computing Systems.
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Instituto Brasileiro de Geografia e Estatística (IBGE) (2021). Estatísticas de gênero: Indicadores sociais das mulheres no brasil. Acesso em: 20 mar. 2025.
McConnell, S. (2004). Code Complete: A Practical Handbook of Software Construction. Microsoft Press.
Murphy-Hill, E., Zimmermann, T., and Nagappan, N. (2014). Cowboys, ankle sprains, and keepers of quality: How is video game development different from software development? In Proceedings of the 36th International Conference on Software Engineering (ICSE).
na Tecnologia Brasil, P. M. (2023). Representação feminina em cargos de liderança no setor de tecnologia.
Rodríguez-Pérez, G., González-Torres, A., García-Holgado, A., and García-Peñalvo, F. J. (2021). A systematic literature review on the influence of gender in the software engineering field. Empirical Software Engineering, 26(3):1–32.
Rosser, S. V. (2004). Women, Gender, and Technology. University of Illinois Press, Urbana and Chicago.
Rosser, S. V. (2005). Through the lens of feminist theory: Focus on women and technology. Frontiers: A Journal of Women Studies, 26(1):1–23.
Roth, L. and Green, E. (2021). Gender bias and the reinforcement of exclusion in software engineering. Diversity in Tech Journal, 5(2):45–58.
Storey, M.-A., Zagalsky, A., Filho, F. F., Singer, L., and German, D. M. (2017). How social and communication channels shape and challenge a participatory culture in software development. IEEE Transactions on Software Engineering.
Terrell, J., Kofink, A., Middleton, J., Rainear, C., Murphy-Hill, E., Parnin, C., and Stallings, J. (2017). Gender differences and bias in open source: Pull request acceptance of women versus men. PeerJ Computer Science, 3:e111.
Vasilescu, B., Capiluppi, A., and Serebrenik, A. (2015). Gender, representation and online participation: A quantitative study of stack overflow. ACM.
Williams, J. C., Phillips, K. W., and Hall, E. (2016). Double Jeopardy? Gender Bias in STEM Professions. Center for WorkLife Law.
World Economic Forum (2023). Global gender gap report 2023. Acesso em: 20 mar. 2025.
Wynn, A. T. and Correll, S. (2018). Puncturing the pipeline: Do technology companies alienate women in recruiting and retention? Harvard Business Review.
Zeller, A. (2005). The impact of program structure on code defects. ACM SIGSOFT Software Engineering Notes.
Published
2025-07-20
How to Cite
SEABRA, Lorena M. V.; BEZERRA, Pamela T. L..
Bridging the Gap: A Data-Driven Analysis of How Traditional Software Engineering Productivity Metrics Overlook Women’s Performance. In: WOMEN IN INFORMATION TECHNOLOGY (WIT), 19. , 2025, Maceió/AL.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2025
.
p. 94-105.
ISSN 2763-8626.
DOI: https://doi.org/10.5753/wit.2025.8364.
