Investigando o Cognitive-Driven Development: Percepções sobre Legibilidade e Manutenção de Código
Resumo
A complexidade do código-fonte impacta diretamente a legibilidade e a manutenção do software. O Cognitive-Driven Development (CDD) é um método que apoia desenvolvedores a controlar a complexidade cognitiva por meio de Pontos de Complexidade Intrínseca (ICPs). Este estudo investigou como o CDD influencia a percepção de legibilidade e manutenção de código. Um survey foi conduzido com 26 desenvolvedores, que avaliaram comparativamente trechos de código. Os resultados indicam que o código desenvolvido sob a influência do CDD foi percebido como mais modular, organizado e fácil de modificar. Entretanto, fatores como experiência e contexto do projeto também têm influenciado as escolhas.Referências
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Palomino, P. T., Fonseca, M., Souza, J., Toda, A. M., Lisboa, R., Cordeiro, T., Pedro, A., and Dermeval, D. (2024). Aprimorando a experiência dos desenvolvedores (devex) para a implementação bem-sucedida de um design system. In Anais do Simpósio Brasileiro de Engenharia de Software (SBES). SBC.
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Pereira, J. H. A., de Souza, A. L. O. T., and Pinto, V. H. S. C. (2021). Cognitive load analyzer: A support tool for cognitive-driven development. In Anais do Simpósio Brasileiro de Engenharia de Software (SBES). ACM.
Pinto, V. H. S. C. and Souza, A. L. O. T. (2022). Effects of cognitive-driven development in the early stages of the software development life cycle. In Proceedings of the 24th International Conference on Enterprise Information Systems (ICEIS). SCITEPRESS.
Pinto, V. H. S. C., Souza, A. L. O. T., de Oliveira, Y. M. B., and Ribeiro, D. M. (2021). Cognitive-driven development: Preliminary results on software refactorings. In Proceedings of the 16th International Conference on Evaluation of Novel Approaches to Software Engineering (ENASE). SCITEPRESS.
Prodanov, C. C. and Freitas, E. C. (2013). Metodologia do Trabalho Científico: Métodos e Técnicas da Pesquisa e do Trabalho Acadêmico. Editora Feevale, Novo Hamburgo, RS, Brasil, 2 edition.
Punter, T., Ciolkowski, M., Freimut, B., and John, I. (2003). Conducting on-line surveys in software engineering. In Proceedings of the 2003 International Symposium on Empirical Software Engineering (ISESE), pages 80–89. IEEE.
Souza, A. L. O. T. and Pinto, V. H. S. C. (2020). Toward a definition of cognitive-driven development. In 2020 IEEE International Conference on Software Maintenance and Evolution (ICSME). IEEE.
Sweller, J. (1988). Cognitive load during problem solving: Effects on learning. Cognitive Science, 12(2):257–285.
Thathsarani, H. A. N. N. and Aluthwaththage, J. H. (2024). A comprehensive metric for evaluating object-oriented software complexity. In 2024 3rd International Conference for Advancement in Technology (ICONAT). IEEE.
Wyrich, M., Preikschat, A., Graziotin, D., and Wagner, S. (2021). The mind is a powerful place: How showing code comprehensibility metrics influences code understanding. In Proceedings of the 43rd International Conference on Software Engineering (ICSE). IEEE/ACM.
McCabe, T. (1976). A complexity measure. IEEE Transactions on Software Engineering, SE-2(4):308–320.
Noda, A., Storey, M.-A., Forsgren, N., and Greiler, M. (2023). Devex: What actually drives productivity: The developer-centric approach to measuring and improving productivity. Queue, 21(2):35–53.
Oliveira, D., Bruno, R., Madeiral, F., and Castor, F. (2020). Evaluating code readability and legibility: An examination of human-centric studies. Proceedings of the 2020 IEEE International Conference on Software Maintenance and Evolution (ICSME).
Palomino, P. T., Fonseca, M., Souza, J., Toda, A. M., Lisboa, R., Cordeiro, T., Pedro, A., and Dermeval, D. (2024). Aprimorando a experiência dos desenvolvedores (devex) para a implementação bem-sucedida de um design system. In Anais do Simpósio Brasileiro de Engenharia de Software (SBES). SBC.
Park, K.-i. (2024). Assessing software developer productivity and emotional state using biometrics. In Proceedings of the 2024 IEEE International Conference on Software Maintenance and Evolution (ICSME). IEEE.
Pereira, J. H. A., de Souza, A. L. O. T., and Pinto, V. H. S. C. (2021). Cognitive load analyzer: A support tool for cognitive-driven development. In Anais do Simpósio Brasileiro de Engenharia de Software (SBES). ACM.
Pinto, V. H. S. C. and Souza, A. L. O. T. (2022). Effects of cognitive-driven development in the early stages of the software development life cycle. In Proceedings of the 24th International Conference on Enterprise Information Systems (ICEIS). SCITEPRESS.
Pinto, V. H. S. C., Souza, A. L. O. T., de Oliveira, Y. M. B., and Ribeiro, D. M. (2021). Cognitive-driven development: Preliminary results on software refactorings. In Proceedings of the 16th International Conference on Evaluation of Novel Approaches to Software Engineering (ENASE). SCITEPRESS.
Prodanov, C. C. and Freitas, E. C. (2013). Metodologia do Trabalho Científico: Métodos e Técnicas da Pesquisa e do Trabalho Acadêmico. Editora Feevale, Novo Hamburgo, RS, Brasil, 2 edition.
Punter, T., Ciolkowski, M., Freimut, B., and John, I. (2003). Conducting on-line surveys in software engineering. In Proceedings of the 2003 International Symposium on Empirical Software Engineering (ISESE), pages 80–89. IEEE.
Souza, A. L. O. T. and Pinto, V. H. S. C. (2020). Toward a definition of cognitive-driven development. In 2020 IEEE International Conference on Software Maintenance and Evolution (ICSME). IEEE.
Sweller, J. (1988). Cognitive load during problem solving: Effects on learning. Cognitive Science, 12(2):257–285.
Thathsarani, H. A. N. N. and Aluthwaththage, J. H. (2024). A comprehensive metric for evaluating object-oriented software complexity. In 2024 3rd International Conference for Advancement in Technology (ICONAT). IEEE.
Wyrich, M., Preikschat, A., Graziotin, D., and Wagner, S. (2021). The mind is a powerful place: How showing code comprehensibility metrics influences code understanding. In Proceedings of the 43rd International Conference on Software Engineering (ICSE). IEEE/ACM.
Publicado
20/07/2025
Como Citar
SANTANA, Michel Sales; ARRUDA, João Pedro Souza; PINTO, Victor Hugo Santiago Costa.
Investigando o Cognitive-Driven Development: Percepções sobre Legibilidade e Manutenção de Código. In: SEMINÁRIO INTEGRADO DE SOFTWARE E HARDWARE (SEMISH), 52. , 2025, Maceió/AL.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2025
.
p. 585-596.
ISSN 2595-6205.
DOI: https://doi.org/10.5753/semish.2025.9259.
