Minerando Conhecimentos de Projetos de Software a partir dos Registros de Comunicação de Desenvolvedores
Resumo
Desenvolvedores de software utilizam diversos canais de comunicação para apoiar o desenvolvimento e gestão de projetos. No entanto, discussões relevantes podem se perder, ser esquecidas ou duplicadas em meio ao grande volume de mensagens, comprometendo o compartilhamento e reuso de conhecimentos. Esta pesquisa investiga como usar métodos automáticos para identificar discussões relevantes nos registros de conversa de desenvolvedores e apoiar a identificação de conhecimentos de projetos de software. Com base na metodologia Design Science Research, foi criado o framework experimental Miner4DevTeam, que viabiliza a identificação de conhecimentos úteis para a evolução do produto e tomada de decisões. Futuramente, serão desenvolvidas estratégias para a gestão de conhecimento de projetos.Referências
Alkadhi, R., Nonnenmacher, M., Guzman, E., and Bruegge, B. (2018). How do developers discuss rationale? In 2018 IEEE 25th International Conference on Software Analysis, Evolution and Reengineering (SANER), pages 357–369. IEEE.
Francois, R., Nada, M., and Hassan, A. (2015). How to extract knowledge from professional e-mails. In 2015 11th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS), pages 687–692. IEEE.
Hevner, A. R. (2007). A three cycle view of design science research. Scandinavian journal of information systems, 19(2):4.
Lima, M., Ahmed, I., Conte, T., Nascimento, E., Oliveira, E., and Gadelha, B. (2019a). Land of lost knowledge: An initial investigation into projects lost knowledge. In 2019 ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM), pages 1–6. IEEE.
Lima, M., Fontão, A., Fernandes, D., Conte, T., and Gadelha, B. (2019b). How are my students going? a tool to analyse students’ interactions on capstone courses. In Brazilian Symposium on Computers in Education (Simpósio Brasileiro de Informática na Educação-SBIE), volume 30, page 1611.
Lima, M., Oliveira, E., Conte, T., and Gadelha, B. (2020). Clouds are heavy! a storm of relevant project-related terms to support newcomers’ onboarding. In Proceedings of the 34th Brazilian Symposium on Software Engineering, SBES 2020, Natal, Brazil, October 19-23, 2020, pages 319–324.
Lima, M., Steinmacher, I., Ford, D., Liu, E., Vorreuter, G., Conte, T., and Gadelha, B. (2023). Looking for related discussions on github discussions. PeerJ Computer Science.
Pei, J., Wu, Y., Qin, Z., Cong, Y., and Guan, J. (2021). Attention-based model for predicting question relatedness on stack overflow. In 2021 IEEE/ACM 18th International Conference on Mining Software Repositories (MSR), pages 97–107. IEEE.
Ren, L., Zhou, S., Kastner, C., and Wasowski, A. (2019). Identifying redundancies in fork-based development. In 2019 IEEE 26th International Conference on Software Analysis, Evolution and Reengineering (SANER), pages 230–241. IEEE.
Storey, M.-A., Zagalsky, A., Figueira Filho, F., Singer, L., and German, D. M. (2016). How social and communication channels shape and challenge a participatory culture in software development. IEEE Transactions on Software Engineering, 43(2):185–204.
Wang, L., Zhang, L., and Jiang, J. (2020). Duplicate question detection with deep learning in stack overflow. IEEE Access, 8:25964–25975.
Zhang, Y., Wu, Y., Wang, T., and Wang, H. (2020). ilinker: a novel approach for issue knowledge acquisition in github projects. World Wide Web, 23(3):1589–1619.
Francois, R., Nada, M., and Hassan, A. (2015). How to extract knowledge from professional e-mails. In 2015 11th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS), pages 687–692. IEEE.
Hevner, A. R. (2007). A three cycle view of design science research. Scandinavian journal of information systems, 19(2):4.
Lima, M., Ahmed, I., Conte, T., Nascimento, E., Oliveira, E., and Gadelha, B. (2019a). Land of lost knowledge: An initial investigation into projects lost knowledge. In 2019 ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM), pages 1–6. IEEE.
Lima, M., Fontão, A., Fernandes, D., Conte, T., and Gadelha, B. (2019b). How are my students going? a tool to analyse students’ interactions on capstone courses. In Brazilian Symposium on Computers in Education (Simpósio Brasileiro de Informática na Educação-SBIE), volume 30, page 1611.
Lima, M., Oliveira, E., Conte, T., and Gadelha, B. (2020). Clouds are heavy! a storm of relevant project-related terms to support newcomers’ onboarding. In Proceedings of the 34th Brazilian Symposium on Software Engineering, SBES 2020, Natal, Brazil, October 19-23, 2020, pages 319–324.
Lima, M., Steinmacher, I., Ford, D., Liu, E., Vorreuter, G., Conte, T., and Gadelha, B. (2023). Looking for related discussions on github discussions. PeerJ Computer Science.
Pei, J., Wu, Y., Qin, Z., Cong, Y., and Guan, J. (2021). Attention-based model for predicting question relatedness on stack overflow. In 2021 IEEE/ACM 18th International Conference on Mining Software Repositories (MSR), pages 97–107. IEEE.
Ren, L., Zhou, S., Kastner, C., and Wasowski, A. (2019). Identifying redundancies in fork-based development. In 2019 IEEE 26th International Conference on Software Analysis, Evolution and Reengineering (SANER), pages 230–241. IEEE.
Storey, M.-A., Zagalsky, A., Figueira Filho, F., Singer, L., and German, D. M. (2016). How social and communication channels shape and challenge a participatory culture in software development. IEEE Transactions on Software Engineering, 43(2):185–204.
Wang, L., Zhang, L., and Jiang, J. (2020). Duplicate question detection with deep learning in stack overflow. IEEE Access, 8:25964–25975.
Zhang, Y., Wu, Y., Wang, T., and Wang, H. (2020). ilinker: a novel approach for issue knowledge acquisition in github projects. World Wide Web, 23(3):1589–1619.
Publicado
04/11/2024
Como Citar
LIMA, Márcia; CONTE, Tayana; STEINMACHER, Igor; GADELHA, Bruno.
Minerando Conhecimentos de Projetos de Software a partir dos Registros de Comunicação de Desenvolvedores. In: WORKSHOP ANUAL DO MPS (WAMPS), 20. , 2024, Salvador/BA.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2024
.
p. 6-10.
DOI: https://doi.org/10.5753/wamps.2024.33364.
