Understanding FLOSS through community publications: strategies for grey literature review (2020)
- Authors:
- USP affiliated authors: KON, FABIO - IME ; WEN, MELISSA SHIHFAN RIBEIRO - IME ; LEITE, LEONARDO ALEXANDRE FERREIRA - IME
- Unidade: IME
- DOI: 10.1145/3377816.3381729
- Subjects: SOFTWARE LIVRE; LINUX; SISTEMAS OPERACIONAIS
- Keywords: grey literature; literature review; FLOSS
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Source:
- Título: Proceedings
- Conference titles: International Conference on Software Engineering - ICSE
- Este periódico é de assinatura
- Este artigo NÃO é de acesso aberto
- Cor do Acesso Aberto: closed
-
ABNT
WEN, Melissa et al. Understanding FLOSS through community publications: strategies for grey literature review. 2020, Anais.. New York: ACM, 2020. Disponível em: https://doi.org/10.1145/3377816.3381729. Acesso em: 27 dez. 2025. -
APA
Wen, M., Leite, L. A. F., Kon, F., & Meirelles, P. (2020). Understanding FLOSS through community publications: strategies for grey literature review. In Proceedings. New York: ACM. doi:10.1145/3377816.3381729 -
NLM
Wen M, Leite LAF, Kon F, Meirelles P. Understanding FLOSS through community publications: strategies for grey literature review [Internet]. Proceedings. 2020 ;[citado 2025 dez. 27 ] Available from: https://doi.org/10.1145/3377816.3381729 -
Vancouver
Wen M, Leite LAF, Kon F, Meirelles P. Understanding FLOSS through community publications: strategies for grey literature review [Internet]. Proceedings. 2020 ;[citado 2025 dez. 27 ] Available from: https://doi.org/10.1145/3377816.3381729 - A survey of DevOps concepts and challenges
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- Building a theory of software teams organization in a continuous delivery context
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- Implantação automatizada de composições de serviços web de grande escala
- A grounded theory of organizational structures for development and infrastructure professionals in software-producing organizations
- Understanding context and forces for choosing organizational structures for continuous delivery
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- Harmonizing DevOps taxonomies: a grounded theory study
Informações sobre o DOI: 10.1145/3377816.3381729 (Fonte: oaDOI API)
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