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An Extended Secondary Study to Characterize the Influence of Developers Sentiments on Practices and Artifacts in Open Source Software Projects

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Enterprise Information Systems (ICEIS 2020)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 417))

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Abstract

Context: Sentiment Analysis applies computational techniques for both automated and semi-automated identification of human behavior. There is a trend to use such techniques in Sentiment Analysis tasks in the Software Engineering context. Objective: Characterize the influence of developers sentiments on software practices and artifacts in open source software projects. Methods: We conducted a Systematic Literature Review (SLR) to identify references in the literature related to the influence of developers sentiments on software practices and artifacts. Results: Evidence showed an increasing number of studies in this theme shedding light on issues related to the influence of developers sentiments on software practices. Practices focusing on developers productivity and collaboration, as well as source code, are the most vulnerable to sentiments variation. Conclusions: Based on the results provided in this SLR, we intend to present an updated and comprehensive overview regarding how the sentiments of developers can positively or negatively impact software practices and artifacts.

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Notes

  1. 1.

    https://github.com/impactsentimentanalysis/iceisExploratoryStudy2020.

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Author information

Authors and Affiliations

  1. Instituto Federal da Bahia (IFBA), Seabra-Bahia, Brazil

    Rui Santos Carigé Júnior

  2. Universidade Salvador (UNIFACS), Salvador-Bahia, Brazil

    Glauco de Figueiredo Carneiro

Authors
  1. Rui Santos Carigé Júnior
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  2. Glauco de Figueiredo Carneiro
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Corresponding author

Correspondence to Glauco de Figueiredo Carneiro .

Editor information

Editors and Affiliations

  1. Polytechnic Institute of Setúbal/INSTICC, Setúbal, Portugal

    Joaquim Filipe

  2. Warsaw University of Technology, Warsaw, Poland

    Michał Śmiałek

  3. George Mason University, Fairfax, VA, USA

    Alexander Brodsky

  4. MODESTE/ESEO, Angers, France

    Slimane Hammoudi

Appendix

Appendix

1.1 A. List of Selected Papers

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SP02 & Asri, I. E., Kerzazi, N., Uddin, G., Khomh, F., and Idrissi, M. J. (2019). An empirical study of sentiments in code reviews. Information and Software Technology, 114:37–54.

SP03 & Graziotin, D., Fagerholm, F., Wang, X., and Abrahamsson, P. (2017). Consequences of unhappiness while developing software. In 2nd IEEE/ACM International Workshop on Emotion Awareness in Software Engineering, SEmotion@ICSE 2017, Buenos Aires, Argentina, May 21, 2017, pages 42–47.

SP04 & Cheruvelil, J. and C. da Silva, B. (2019). Developers’ sentiment and issue reopening. In 2019 IEEE/ACM 4th International Workshop on Emotion Awareness in Software Engineering (SEmotion), pages 29–33.

SP05 & Ortu, M., Hall, T., Marchesi, M., Tonelli, R., Bowes, D., and Destefanis, G. (2018). Mining communication patterns in software development: A github analysis. In Proceedings of the 14th International Conference on Predictive Models and Data Analytics in Software Engineering, PROMISE’18, pages 70–79, New York, NY, USA. ACM.

SP06 & Zhang, Y., Shen, B., and Chen, Y. (2014). Mining developer mailing list to predict software defects. In 2014 21st Asia-Pacific Software Engineering Conference, volume 1, pages 383–390.

SP07 & Yang, B., Wei, X., and Liu, C. (2017). Sentiments analysis in github repositories: An empirical study. In 2017 24th Asia-Pacific Software Engineering Conference Workshops (APSECW), pages 84–89.

SP08 & Wang, Y. and Redmiles, D. (2016). The diffusion of trust and cooperation in teams with individuals’ variations on baseline trust. In Proceedings of the 19th ACM Conference on Computer-Supported Cooperative Work & Social Computing, CSCW ’16, pages 303–318, New York, NY, USA. ACM.

SP09 & Islam, M. R. and Zibran, M. F. (2016). Towards understanding and exploiting developers’ emotional variations in software engineering. In 2016 IEEE 14th International Conference on Software Engineering Research, Management and Applications (SERA), pages 185–192.

SP10 & Graziotin, D., Fagerholm, F., Wang, X., and Abrahamsson, P. (2018). What happens when software developers are (un)happy. Journal of Systems and Software, 140:32–47.

SP11 & Borges, H. and Valente, M. T. (2018). What’s in a github star? understanding repository starring practices in a social coding platform. Journal of Systems and Software, 146:112–129.

SP12 & Huq, Syed Fatiul, Ali Zafar Sadiq, and Kazi Sakib. (2020). Is Developer Sentiment Related to Software Bugs: An Exploratory Study on GitHub Commits. In 2020 IEEE 27th International Conference on Software Analysis, Evolution and Reengineering (SANER), pp. 527–531. IEEE, 2020.

SP13 & Madampe, K., Hoda, R. and Singh, P., 2020. Towards Understanding Emotional Response to Requirements Changes in Agile Teams. In New Ideas and Emerging Results track of the 42nd IEEE/ACM International Conference on Software Engineering, ICSE2020.

SP14 & Alami, A., Cohn, M.L. and Wąsowski, A., 2019, May. Why does code review work for open source software communities? In 2019 IEEE/ACM 41st International Conference on Software Engineering (ICSE) (pp. 1073–1083). IEEE.

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Júnior, R.S.C., Carneiro, G.d.F. (2021). An Extended Secondary Study to Characterize the Influence of Developers Sentiments on Practices and Artifacts in Open Source Software Projects. In: Filipe, J., Śmiałek, M., Brodsky, A., Hammoudi, S. (eds) Enterprise Information Systems. ICEIS 2020. Lecture Notes in Business Information Processing, vol 417. Springer, Cham. https://doi.org/10.1007/978-3-030-75418-1_16

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  • DOI: https://doi.org/10.1007/978-3-030-75418-1_16

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