Understanding and measuring software engineer behavior: What can we learn from the behavioral sciences?
Resumo
This paper explores the intricate challenge of understanding and measuring software engineer behavior. More specifically, we revolve around a central question: How can we enhance our understanding of software engineer behavior? Grounded in the nuanced complexities addressed within Behavioral Software Engineering (BSE), we advocate for holistic methods that integrate quantitative measures, such as psychometric instruments, and qualitative data from diverse sources. Furthermore, we delve into the relevance of this challenge within national and international contexts, highlighting the increasing interest in understanding software engineer behavior. Real-world initiatives and academic endeavors are also examined to underscore the potential for advancing this research agenda and, consequently, refining software engineering practices based on behavioral aspects. Lastly, this paper addresses different ways to evaluate the progress of this challenge by leveraging methodological skills derived from behavioral sciences, ultimately contributing to a deeper understanding of software engineer behavior and software engineering practices.Referências
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Guenes, P., Tomaz, R., Kalinowski, M., Baldassarre, M. T., and Storey, M.-A. (2023). Impostor phenomenon in software engineers. arXiv preprint arXiv:2312.03966.
Guimarães, G., Perkusich, M., Albuquerque, D., Guimaraes, E., Almeida, H., Santos, D., and Perkusich, A. (2021). A comparative study of psychometric instruments in software engineering. In International Conference on Software Engineering and Knowledge Engineering, SEKE, volume 2021, pages 229–234.
Johnson, B. and Menzies, T. (2023). Ethics: Why software engineers can’t afford to look away. IEEE Software, 41(1):142–144.
Kurian, R. M. and Thomas, S. (2023). Importance of positive emotions in software developers’ performance: a narrative review. Theoretical Issues in Ergonomics Science, 24(6):631–645.
Lenberg, P., Feldt, R., Gren, L., Wallgren Tengberg, L. G., Tidefors, I., and Graziotin, D. (2023). Qualitative software engineering research: Reflections and guidelines. Journal of Software: Evolution and Process.
Lenberg, P., Feldt, R., and Wallgren, L.-G. (2014). Towards a behavioral software engineering. In Proceedings of the 7th international workshop on cooperative and human aspects of software engineering.
Lenberg, P., Feldt, R., and Wallgren, L. G. (2015). Behavioral software engineering: A definition and systematic literature review. Journal of Systems and software, 107:15–37.
Lincoln, Y. S. and Guba, E. G. (1985). Naturalistic inquiry. sage.
Maxwell, J. (1992). Understanding and validity in qualitative research. Harvard educational review, 62(3):279–301.
McConnell, J. V. (1974). Understanding human behavior: An introduction to psychology. Holt, Rinehart & Winston.
Molléri, J. S., Petersen, K., and Mendes, E. (2018). Towards understanding the relation between citations and research quality in software engineering studies. Scientometrics, 117:1453–1478.
Ogundare, O. (2017). How do you know what you know: Epistemology in software engineering. Journal of Software Engineering and Applications, 10(2):168–173.
Petre, M., Buckley, J., Church, L., Storey, M.-A., and Zimmermann, T. (2020). Behavioral science of software engineering. IEEE Software, 37(6):21–25.
Sandelowski, M. (1986). The problem of rigor in qualitative research. Advances in nursing science.
Schoenherr, J. R. and Hamstra, S. J. (2016). Psychometrics and its discontents: An historical perspective on the discourse of the measurement tradition. Advances in health sciences education, 21:719–729.
Skinner, B. F. (1965). Science and human behavior. Number 92904. Simon and Schuster.
Tulili, T. R., Capiluppi, A., and Rastogi, A. (2023). Burnout in software engineering: A systematic mapping study. Information and Software Technology, 155:107116.
Watson, J. B. (2017). Behaviorism. Routledge.
Wilder, D. A., Austin, J., and Casella, S. (2009). Applying behavior analysis in organizations: Organizational behavior management. Psychological Services, 6(3):202.
Carter, I. (2017). Human behavior in the social environment: A social systems approach. Routledge.
Carver, J. C., Muccini, H., Penzenstadler, B., Prikladnicki, R., Serebrenik, A., and Zimmermann, T. (2021). Behavioral science and diversity in software engineering. IEEE Software, 38(2):107–112.
Feldt, R., Torkar, R., Angelis, L., and Samuelsson, M. (2008). Towards individualized software engineering: empirical studies should collect psychometrics. In Proceedings of the 2008 international workshop on Cooperative and human aspects of software engineering, pages 49–52.
Felipe, D. A., Kalinowski, M., Graziotin, D., and Natividade, J. C. (2023). Psychometric instruments in software engineering research on personality: Status quo after fifty years. Journal of Systems and Software, 203:111740.
Furr, R. M. (2021). Psychometrics: an introduction. SAGE publications.
Graziotin, D. and Fagerholm, F. (2019). Happiness and the productivity of software engineers. Rethinking Productivity in Software Engineering, pages 109–124.
Graziotin, D., Lenberg, P., Feldt, R., and Wagner, S. (2022). Psychometrics in Behavioral Software Engineering: A Methodological Introduction with Guidelines. ACM Transactions on Software Engineering and Methodology, 31(1):1–36.
Graziotin, D., Wang, X., and Abrahamsson, P. (2015). The affect of software developers: common misconceptions and measurements. In 2015 IEEE/ACM 8th International Workshop on Cooperative and Human Aspects of Software Engineering, pages 123–124. IEEE.
Gren, L. (2018). Standards of validity and the validity of standards in behavioral software engineering research: the perspective of psychological test theory. In Proceedings of the 12th ACM/IEEE international symposium on empirical software engineering and measurement, pages 1–4.
Gren, L. and Goldman, A. (2016). Useful statistical methods for human factors research in software engineering: a discussion on validation with quantitative data. In Proceedings of the 9th International Workshop on Cooperative and Human Aspects of Software Engineering, pages 121–124.
Guenes, P., Tomaz, R., Kalinowski, M., Baldassarre, M. T., and Storey, M.-A. (2023). Impostor phenomenon in software engineers. arXiv preprint arXiv:2312.03966.
Guimarães, G., Perkusich, M., Albuquerque, D., Guimaraes, E., Almeida, H., Santos, D., and Perkusich, A. (2021). A comparative study of psychometric instruments in software engineering. In International Conference on Software Engineering and Knowledge Engineering, SEKE, volume 2021, pages 229–234.
Johnson, B. and Menzies, T. (2023). Ethics: Why software engineers can’t afford to look away. IEEE Software, 41(1):142–144.
Kurian, R. M. and Thomas, S. (2023). Importance of positive emotions in software developers’ performance: a narrative review. Theoretical Issues in Ergonomics Science, 24(6):631–645.
Lenberg, P., Feldt, R., Gren, L., Wallgren Tengberg, L. G., Tidefors, I., and Graziotin, D. (2023). Qualitative software engineering research: Reflections and guidelines. Journal of Software: Evolution and Process.
Lenberg, P., Feldt, R., and Wallgren, L.-G. (2014). Towards a behavioral software engineering. In Proceedings of the 7th international workshop on cooperative and human aspects of software engineering.
Lenberg, P., Feldt, R., and Wallgren, L. G. (2015). Behavioral software engineering: A definition and systematic literature review. Journal of Systems and software, 107:15–37.
Lincoln, Y. S. and Guba, E. G. (1985). Naturalistic inquiry. sage.
Maxwell, J. (1992). Understanding and validity in qualitative research. Harvard educational review, 62(3):279–301.
McConnell, J. V. (1974). Understanding human behavior: An introduction to psychology. Holt, Rinehart & Winston.
Molléri, J. S., Petersen, K., and Mendes, E. (2018). Towards understanding the relation between citations and research quality in software engineering studies. Scientometrics, 117:1453–1478.
Ogundare, O. (2017). How do you know what you know: Epistemology in software engineering. Journal of Software Engineering and Applications, 10(2):168–173.
Petre, M., Buckley, J., Church, L., Storey, M.-A., and Zimmermann, T. (2020). Behavioral science of software engineering. IEEE Software, 37(6):21–25.
Sandelowski, M. (1986). The problem of rigor in qualitative research. Advances in nursing science.
Schoenherr, J. R. and Hamstra, S. J. (2016). Psychometrics and its discontents: An historical perspective on the discourse of the measurement tradition. Advances in health sciences education, 21:719–729.
Skinner, B. F. (1965). Science and human behavior. Number 92904. Simon and Schuster.
Tulili, T. R., Capiluppi, A., and Rastogi, A. (2023). Burnout in software engineering: A systematic mapping study. Information and Software Technology, 155:107116.
Watson, J. B. (2017). Behaviorism. Routledge.
Wilder, D. A., Austin, J., and Casella, S. (2009). Applying behavior analysis in organizations: Organizational behavior management. Psychological Services, 6(3):202.
Publicado
21/07/2024
Como Citar
ARAÚJO, Allysson Allex; KALINOWSKI, Marcos; GRAZIOTIN, Daniel.
Understanding and measuring software engineer behavior: What can we learn from the behavioral sciences?. In: WORKSHOP SOBRE ASPECTOS SOCIAIS, HUMANOS E ECONÔMICOS DE SOFTWARE (WASHES), 9. , 2024, Brasília/DF.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2024
.
p. 175-180.
ISSN 2763-874X.
DOI: https://doi.org/10.5753/washes.2024.2986.
