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Artigo de periodico
Learning by sampling: learning behavioral family models from software product lines (2021)
Damasceno, Carlos Diego Nascimento ; Mousavi, Mohammad Reza ; Simão, Adenilso da Silva
Source: Empirical Software Engineering. Unidade: ICMC
Subjects: MODELOS DE PROCESSO DE SOFTWARE, APRENDIZADO COMPUTACIONAL
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ABNT
DAMASCENO, Carlos Diego Nascimento e MOUSAVI, Mohammad Reza e SIMÃO, Adenilso da Silva. Learning by sampling: learning behavioral family models from software product lines. Empirical Software Engineering, v. 26, n. Ja 2021, p. 1-46, 2021Tradução . . Disponível em: https://doi.org/10.1007/s10664-020-09912-w. Acesso em: 26 jul. 2024.
APA
Damasceno, C. D. N., Mousavi, M. R., & Simão, A. da S. (2021). Learning by sampling: learning behavioral family models from software product lines. Empirical Software Engineering, 26( Ja 2021), 1-46. doi:10.1007/s10664-020-09912-w
NLM
Damasceno CDN, Mousavi MR, Simão A da S. Learning by sampling: learning behavioral family models from software product lines [Internet]. Empirical Software Engineering. 2021 ; 26( Ja 2021): 1-46.[citado 2024 jul. 26 ] Available from: https://doi.org/10.1007/s10664-020-09912-w
Vancouver
Damasceno CDN, Mousavi MR, Simão A da S. Learning by sampling: learning behavioral family models from software product lines [Internet]. Empirical Software Engineering. 2021 ; 26( Ja 2021): 1-46.[citado 2024 jul. 26 ] Available from: https://doi.org/10.1007/s10664-020-09912-w
Tese (Doutorado)
Learning finite state machine models of evolving systems: From evolution over time to variability in space (2020)
Damasceno, Carlos Diego Nascimento; Mousavi, Mohammad Reza (Orientador); Simão, Adenilso da Silva (Orientador)
Unidade: ICMC
Subjects: ENGENHARIA DE SOFTWARE, SOFTWARES
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
DAMASCENO, Carlos Diego Nascimento. Learning finite state machine models of evolving systems: From evolution over time to variability in space. 2020. Tese (Doutorado) – Universidade de São Paulo, São Carlos, 2020. Disponível em: https://www.teses.usp.br/teses/disponiveis/55/55134/tde-02092020-091958/. Acesso em: 26 jul. 2024.
APA
Damasceno, C. D. N. (2020). Learning finite state machine models of evolving systems: From evolution over time to variability in space (Tese (Doutorado). Universidade de São Paulo, São Carlos. Recuperado de https://www.teses.usp.br/teses/disponiveis/55/55134/tde-02092020-091958/
NLM
Damasceno CDN. Learning finite state machine models of evolving systems: From evolution over time to variability in space [Internet]. 2020 ;[citado 2024 jul. 26 ] Available from: https://www.teses.usp.br/teses/disponiveis/55/55134/tde-02092020-091958/
Vancouver
Damasceno CDN. Learning finite state machine models of evolving systems: From evolution over time to variability in space [Internet]. 2020 ;[citado 2024 jul. 26 ] Available from: https://www.teses.usp.br/teses/disponiveis/55/55134/tde-02092020-091958/
Trabalho de evento
Learning from difference: an automated approach for learning family models from software product lines (2019)
Damasceno, Carlos Diego Nascimento ; Mousavi, Mohammad Reza; Simão, Adenilso da Silva
Source: Proceedings. Conference titles: International Systems and Software Product Line Conference - SPLC. Unidade: ICMC
Subjects: TESTE E AVALIAÇÃO DE SOFTWARE, APRENDIZAGEM, MODELOS DE PROCESSO DE SOFTWARE
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
DAMASCENO, Carlos Diego Nascimento e MOUSAVI, Mohammad Reza e SIMÃO, Adenilso da Silva. Learning from difference: an automated approach for learning family models from software product lines. 2019, Anais.. New York: ACM, 2019. Disponível em: https://doi.org/10.1145/3336294.3336307. Acesso em: 26 jul. 2024.
APA
Damasceno, C. D. N., Mousavi, M. R., & Simão, A. da S. (2019). Learning from difference: an automated approach for learning family models from software product lines. In Proceedings (Vol. A). New York: ACM. doi:10.1145/3336294.3336307
NLM
Damasceno CDN, Mousavi MR, Simão A da S. Learning from difference: an automated approach for learning family models from software product lines [Internet]. Proceedings. 2019 ; A[citado 2024 jul. 26 ] Available from: https://doi.org/10.1145/3336294.3336307
Vancouver
Damasceno CDN, Mousavi MR, Simão A da S. Learning from difference: an automated approach for learning family models from software product lines [Internet]. Proceedings. 2019 ; A[citado 2024 jul. 26 ] Available from: https://doi.org/10.1145/3336294.3336307
Trabalho de evento-anais periodico
Learning to reuse: adaptive model learning for evolving systems (2019)
Damasceno, Carlos Diego Nascimento ; Mousavi, Mohammad Reza ; Simão, Adenilso da Silva
Source: Lecture Notes in Computer Science - LNCS. Conference titles: International Conference on Integrated Formal Methods - IFM. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, ALGORITMOS, REÚSO DE SOFTWARE
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
DAMASCENO, Carlos Diego Nascimento e MOUSAVI, Mohammad Reza e SIMÃO, Adenilso da Silva. Learning to reuse: adaptive model learning for evolving systems. Lecture Notes in Computer Science - LNCS. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-030-34968-4_8. Acesso em: 26 jul. 2024. , 2019
APA
Damasceno, C. D. N., Mousavi, M. R., & Simão, A. da S. (2019). Learning to reuse: adaptive model learning for evolving systems. Lecture Notes in Computer Science - LNCS. Cham: Springer. doi:10.1007/978-3-030-34968-4_8
NLM
Damasceno CDN, Mousavi MR, Simão A da S. Learning to reuse: adaptive model learning for evolving systems [Internet]. Lecture Notes in Computer Science - LNCS. 2019 ; 11918 138-156.[citado 2024 jul. 26 ] Available from: https://doi.org/10.1007/978-3-030-34968-4_8
Vancouver
Damasceno CDN, Mousavi MR, Simão A da S. Learning to reuse: adaptive model learning for evolving systems [Internet]. Lecture Notes in Computer Science - LNCS. 2019 ; 11918 138-156.[citado 2024 jul. 26 ] Available from: https://doi.org/10.1007/978-3-030-34968-4_8
Dissertação (Mestrado)
Evaluating finite state machine based testing methods on RBAC systems (2016)
Damasceno, Carlos Diego Nascimento; Simão, Adenilso da Silva (Orientador)
Unidade: ICMC
Subjects: SOFTWARES, SISTEMAS DE INFORMAÇÃO, ENGENHARIA DE SOFTWARE
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
DAMASCENO, Carlos Diego Nascimento. Evaluating finite state machine based testing methods on RBAC systems. 2016. Dissertação (Mestrado) – Universidade de São Paulo, São Carlos, 2016. Disponível em: http://www.teses.usp.br/teses/disponiveis/55/55134/tde-11112016-101158/. Acesso em: 26 jul. 2024.
APA
Damasceno, C. D. N. (2016). Evaluating finite state machine based testing methods on RBAC systems (Dissertação (Mestrado). Universidade de São Paulo, São Carlos. Recuperado de http://www.teses.usp.br/teses/disponiveis/55/55134/tde-11112016-101158/
NLM
Damasceno CDN. Evaluating finite state machine based testing methods on RBAC systems [Internet]. 2016 ;[citado 2024 jul. 26 ] Available from: http://www.teses.usp.br/teses/disponiveis/55/55134/tde-11112016-101158/
Vancouver
Damasceno CDN. Evaluating finite state machine based testing methods on RBAC systems [Internet]. 2016 ;[citado 2024 jul. 26 ] Available from: http://www.teses.usp.br/teses/disponiveis/55/55134/tde-11112016-101158/

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