Finding Collaborations based on Co-Changed Files

  • Kattiana Constantino UFMG
  • Eduardo Figueiredo UFMG

Resumo


A colaboração é essencial no desenvolvimento de software, porém encontrar colaboradores adequados pode ser um desafio em grandes projetos de código aberto. Neste trabalho, investigamos o desenvolvimento colaborativo de código com base em interesses similares para ajudar os desenvolvedores a encontrar colaboradores adequados. Cinco estudos empíricos foram conduzidos, incluindo entrevistas e questionários. Duas estratégias baseadas em arquivos co-alterados e um protótipo denominada COOPFINDER foram propostas e avaliadas. Usuários ou não do GitHub acharam as estratégias e a ferramenta úteis. Os resultados sugerem que promover colaborações em projetos pode evitar o desperdício de recursos e manter a continuidade do projeto.

Referências

Avelino, G., Passos, L., Hora, A., and Valente, M. T. (2016). A novel approach for estimating truck factors. Proc. of the 24th Int. Conf. on Prog. Comp. (ICPC), pages 1–10. IEEE.

Basili, V. R. and Weiss, D. M. (1984). A methodology for collecting valid software engineering data. IEEE Trans. on Soft. Eng. (TSE), (6):728–738.

Canfora, G., Di Penta, M., Oliveto, R., and Panichella, S. (2012). Who is going to mentor newcomers in open source projects? Proc. of the 20th Int. Sym. on the Foundations of Soft. Eng. (FSE), pages 1–11.

Constantino, K., Belém, F., and Figueiredo, E. (2023a). Dual analysis for helping developers to find collaborators based on co-changed files: An empirical study. J. of Soft.: Pract. and Exp., pages 1–27.

Constantino, K. and Figueiredo, E. (2022). Coopfinder: Finding collaborators based on co–changed files. Proc. of the IEEE Sym. on Vis. Lang. and H-Centric Comp. (VL/HCC), pages 1–3. IEEE.

Constantino, K., Prates, R., and Figueiredo, E. (2023b). Recommending collaborators based on co–changed files: A controlled experiment. In Anais do XVIII Simpósio Brasileiro de Sistemas Colaborativos.

Constantino, K., Souza, M., Zhou, S., Figueiredo, E., and Kästner, C. (2021). Perceptions of open-source software developers on collaborations: An interview and survey study. J. of Soft.: Evol. and Proc., 33:e2393.

Constantino, K., Zhou, S., Souza, M., Figueiredo, E., and Kästner, C. (2020). Understanding collaborative software development: An interview study. Proc. of the 15th Int. Conf. on Global Soft. Eng. (ICGSE), page 55–65. Assoc. for Comp. Mach.

Corbin, J. and Strauss, A. (2014). Basics of Qualitative Research: Techniques and Procedures for Developing Grounded Theory. Sage Publications, Inc Thousand Oaks.

Costa, C., Figueirêdo, J., Pimentel, J. F., Sarma, A., and Murta, L. (2021). Recommending participants for collaborative merge sessions. IEEE Trans. on Soft. Eng., 47(6):1198–1210.

Creswell, J. W. and Creswell, J. D. (2017). Research Design: Qualitative, Quantitative, and Mixed Methods Approaches. SAGE Publications.

Easterbrook, S., Singer, J., Storey, M.-A., and Damian, D. (2008). Selecting empirical methods for software engineering research. In Guide to Adv. Emp. Soft. Eng., pages 285–311. Springer.

Ferreira, M., Valente, M. T., and Ferreira, K. (2017). A comparison of three algorithms for computing truck factors. Proc. of the 25th Int. Conf. on Prog. Comp. (ICPC), pages 207–217. IEEE.

Fisher, R. A. (1992). The arrangement of field experiments. In Breakthroughs in statistics, pages 82–91.

Gamalielsson, J. and Lundell, B. (2014). Sustainability of open source software communities beyond a fork: How and why has the libreoffice project evolved? J. of Sys. and Soft., 89:128–145.

Gousios, G., Pinzger, M., and Deursen, A. v. (2014). An exploratory study of the pullbased software development model. Proc. of the 36th Int. Conf. on Soft. Eng. (ICSE), pages 345–355.

Gousios, G., Zaidman, A., Storey, M.-A., and Deursen, A. v. (2015). Work practices and challenges in pull-based development: The integrator’s perspective. Proc. of the 37th Int. Conf. on Soft. Eng. (ICSE), pages 358–368.

Jiang, J., He, J.-H., and Chen, X.-Y. (2015). Coredevrec: Automatic core member recommendation for contribution evaluation. J. of Comp. Sci. and Tech., 30(5):998–1016.

Kononenko, O., Baysal, O., and Godfrey, M. W. (2016). Code review quality: How developers see it. Proc. of the 38th Int. Conf. on Soft. Eng. (ICSE), pages 1028–1038.

Minto, S. and Murphy, G. C. (2007). Recommending emergent teams. Proc. of the 4th Int. Conf. on Mining Software Repositories (MSR), pages 5–5. IEEE.

Pfleeger, S. L. and Kitchenham, B. A. (2001). Principles of survey research part 1: Turning lemons into lemonade. SIGSOFT Soft. Eng. Notes, 26(6):16–18.

Pham, R., Singer, L., Liskin, O., Figueira Filho, F., and Schneider, K. (2013). Creating a shared understanding of testing culture on a social coding site. Proc. of the 35th Int. Conf. on Soft. Eng. (ICSE), pages 112–121. IEEE.

Pinto, G., Steinmacher, I., and Gerosa, M. (2016). More common than you think: An in-depth study of casual contributors. Proc. of the 23rd Int. Conf. on Soft. Analysis, Evolution, and Reengineering (SANER), pages 112–123. IEEE.

Salton, G. (1989). Automatic text processing: The transformation, analysis, and retrieval of. Reading: Addison-Wesley, 169.

Steinmacher, I., Pinto, G., Wiese, I. S., and Gerosa, M. A. (2018). Almost there: A study on quasi-contributors in open-source software projects. Proc. of the 40th Int. Conf. on Soft. Eng. (ICSE), pages 256–266. IEEE.

Tamburri, D. A., Kruchten, P., Lago, P., and Van Vliet, H. (2015). Social debt in software engineering: Insights from industry. J. of Int. Serv. and App., 6(1):1–17.

Yu, Y., Wang, H., Filkov, V., Devanbu, P., and Vasilescu, B. (2015). Wait for it: Determinants of pull request evaluation latency on github. Proc. of the 12th Int. Conf. on Mining Software Repositories (MSR), pages 367–371. IEEE.
Publicado
22/05/2023
CONSTANTINO, Kattiana; FIGUEIREDO, Eduardo. Finding Collaborations based on Co-Changed Files. In: CONCURSO DE TESES E DISSERTAÇÕES EM SISTEMAS COLABORATIVOS - SIMPÓSIO BRASILEIRO DE SISTEMAS COLABORATIVOS (SBSC), 18. , 2023, Rio de Janeiro/RJ. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2023 . p. 57-66. DOI: https://doi.org/10.5753/sbsc_estendido.2023.229735.