Cost Estimation for Agile Software Development in Small and Medium-Sized Enterprises
Resumo
Problema: A adoção de metodologias ágeis combinada com a gestão financeira e estimativa de custos representa um desafio significativo para pequenas e médias empresas (PMEs). Métodos: Foi realizada uma revisão sistemática da literatura para identificar os principais desafios na estimativa de custos, estratégias para superá-los e ferramentas utilizadas. A partir disso, analisou-se a aplicação de modelos de estimativa em ambientes ágeis. Resultados: Será desenvolvido um modelo específico de estimativa de custos para PMEs, acompanhado de diretrizes práticas para sua implementação. Este estudo contribui para a melhoria da gestão financeira em ambientes ágeis, promovendo práticas alinhadas às necessidades das PMEs. Para uma demonstração visual completa dos conceitos discutidos, o leitor é convidado a acessar o vídeo complementar de até 5 minutos disponível em: https://www.youtube.com/watch?v=1V_hiLzf0gI
Referências
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Arora, M., Verma, S., Kavita, Wozniak, M., Shafi, J., and Ijaz, M. F. (2022). An efficient anfis-eebat approach to estimate efort of scrum projects. Scientific Reports, 12(1):02–14.
Boehm, B. W., Clark, B., Horowitz, E., Westland, C., Madachy, R., and Selby, R. (1995). Cost models for future software life cycle processes: Cocomo 2.0. Annals of Software Engineering, 1:57–94.
Butt, S. A., Ercan, T., Binsawad, M., Ariza-Colpas, P.-P., Diaz-Martinez, J., Pineres-Espitia, G., De-La-Hoz-Franco, E., Melo, M. A. P., Ortega, R. M., and De-La-Hoz-Hernández, J.-D. (2023). Prediction based cost estimation technique in agile development. Advances in engineering software, 175:01–12.
Choudhari, J. and Suman, U. (2012). Story points based effort estimation model for software maintenance. Procedia Technology, 4:761–765.
Fernández-Diego, M., Méndez, E. R., González-Ladrón-De-Guevara, F., Abrahão, S., and Insfran, E. (2020). An update on effort estimation in agile software development: A systematic literature review. IEEE Access, 8:68–100.
Gandomani, T. J., Faraji, H., and Radnejad, M. (2019). Planning poker in cost estimation in agile methods: Averaging vs. consensus. In 2019 5th Conference on Knowledge Based Engineering and Innovation (KBEI), pages 066–071. IEEE.
Khan, J. A., Khan, S. U. R., Khan, T. A., and Khan, I. U. R. (2021). An amplified cocomo-ii based cost estimation model in global software development context. IEEE Access, 9:88602–88620.
Kitchenham, B., Pretorius, R., Budgen, D., Brereton, O. P., Turner, M., Niazi, M., and Linkman, S. (2010). Systematic literature reviews in software engineering: A tertiary study. Information and Software Technology, 52(8):792–805.
Komala, C., Sowmya, H., Aruna, R., Kumar, A., Maranan, R., Medikondu, N. R., Rajaram, A., et al. (2023). Innovative cost estimation for agile technology: A novel energy storage technique incorporating modified planning poker. International Journal of Renewable Energy Research (IJRER), 13(4):1646–1660.
Lee, I. (2021). Pricing and profit management models for saas providers and iaas providers. Journal of Theoretical and Applied Electronic Commerce Research, 16(4):859–873.
Najm, A., Zakrani, A., and Marzak, A. (2023). Efficient shapely explanation of support vector regression for agile and non-agile software effort estimation. In Intelligent Sustainable Systems: Selected Papers of WorldS4 2022, Volume 2, pages 711–729. Springer.
Parsifal (2018). Systematic literature review tool. Accessed: 01.5.2024. [Pasuksmit et al. 2024] Pasuksmit, J., Thongtanunam, P., and Karunasekera, S. (2024). A systematic literature review on reasons and approaches for accurate effort estimations in agile. ACM Computing Surveys.
PRODAM-SP (2024). Edital de pregão eletrônico no 09.004/2024 (compras.gov 99004/2024). [link]. Acesso em: 03 set. 2025.
Putri, R. R., Siahaan, D. O., and Fatichah, C. (2021). Improve the accuracy of software project effort and cost estimates in cocomo ii using gwo. In 2021 5th International Conference on Informatics and Computational Sciences (ICICoS), pages 128–133. IEEE.
Ramessur, M. A. and Nagowah, S. D. (2021). A predictive model to estimate effort in a sprint using machine learning techniques. International Journal of Information Technology, 13(3):02–10.
Rindell, K., Ruohonen, J., Holvitie, J., Hyrynsalmi, S., and Leppänen, V. (2021). Security in agile software sevelopment: A practitioner survey. Information and Software Technology, 131:106488.
Robles, B. D. V., Lara, I. L. A., Salgado, R. S., and Hidalgo-Reyes, M. (2023). Identification of methods, approaches, and factors in effort estimation for devops projects: A systematic literature mapping. In 2023 Mexican International Conference on Computer Science (ENC), pages 1–6. IEEE.
Rodríguez Sánchez, E., Vázquez Santacruz, E. F., and Cervantes Maceda, H. (2023). Effort and cost estimation using decision tree techniques and story points in agile software development. Mathematics, 11(6):1477.
Tawosi, V., Al-Subaihin, A., Moussa, R., and Sarro, F. (2022). A versatile dataset of agile open source software projects. In Proceedings of the 19th International Conference on Mining Software Repositories, pages 707–711.
Usman, M., Mendes, E., Weidt, F., and Britto, R. (2014). Effort estimation in agile software development: a systematic literature review. In Proceedings of the 10th international conference on predictive models in software engineering, PROMISE ’14, pages 82–91, New York, NY, USA. Association for Computing Machinery.
Van Solingen, R. and Berghout, E. W. (1999). The Goal/Question/Metric Method: a practical guide for quality improvement of software development. McGraw-Hill.
Arora, M., Verma, S., Kavita, Wozniak, M., Shafi, J., and Ijaz, M. F. (2022). An efficient anfis-eebat approach to estimate efort of scrum projects. Scientific Reports, 12(1):02–14.
Boehm, B. W., Clark, B., Horowitz, E., Westland, C., Madachy, R., and Selby, R. (1995). Cost models for future software life cycle processes: Cocomo 2.0. Annals of Software Engineering, 1:57–94.
Butt, S. A., Ercan, T., Binsawad, M., Ariza-Colpas, P.-P., Diaz-Martinez, J., Pineres-Espitia, G., De-La-Hoz-Franco, E., Melo, M. A. P., Ortega, R. M., and De-La-Hoz-Hernández, J.-D. (2023). Prediction based cost estimation technique in agile development. Advances in engineering software, 175:01–12.
Choudhari, J. and Suman, U. (2012). Story points based effort estimation model for software maintenance. Procedia Technology, 4:761–765.
Fernández-Diego, M., Méndez, E. R., González-Ladrón-De-Guevara, F., Abrahão, S., and Insfran, E. (2020). An update on effort estimation in agile software development: A systematic literature review. IEEE Access, 8:68–100.
Gandomani, T. J., Faraji, H., and Radnejad, M. (2019). Planning poker in cost estimation in agile methods: Averaging vs. consensus. In 2019 5th Conference on Knowledge Based Engineering and Innovation (KBEI), pages 066–071. IEEE.
Khan, J. A., Khan, S. U. R., Khan, T. A., and Khan, I. U. R. (2021). An amplified cocomo-ii based cost estimation model in global software development context. IEEE Access, 9:88602–88620.
Kitchenham, B., Pretorius, R., Budgen, D., Brereton, O. P., Turner, M., Niazi, M., and Linkman, S. (2010). Systematic literature reviews in software engineering: A tertiary study. Information and Software Technology, 52(8):792–805.
Komala, C., Sowmya, H., Aruna, R., Kumar, A., Maranan, R., Medikondu, N. R., Rajaram, A., et al. (2023). Innovative cost estimation for agile technology: A novel energy storage technique incorporating modified planning poker. International Journal of Renewable Energy Research (IJRER), 13(4):1646–1660.
Lee, I. (2021). Pricing and profit management models for saas providers and iaas providers. Journal of Theoretical and Applied Electronic Commerce Research, 16(4):859–873.
Najm, A., Zakrani, A., and Marzak, A. (2023). Efficient shapely explanation of support vector regression for agile and non-agile software effort estimation. In Intelligent Sustainable Systems: Selected Papers of WorldS4 2022, Volume 2, pages 711–729. Springer.
Parsifal (2018). Systematic literature review tool. Accessed: 01.5.2024. [Pasuksmit et al. 2024] Pasuksmit, J., Thongtanunam, P., and Karunasekera, S. (2024). A systematic literature review on reasons and approaches for accurate effort estimations in agile. ACM Computing Surveys.
PRODAM-SP (2024). Edital de pregão eletrônico no 09.004/2024 (compras.gov 99004/2024). [link]. Acesso em: 03 set. 2025.
Putri, R. R., Siahaan, D. O., and Fatichah, C. (2021). Improve the accuracy of software project effort and cost estimates in cocomo ii using gwo. In 2021 5th International Conference on Informatics and Computational Sciences (ICICoS), pages 128–133. IEEE.
Ramessur, M. A. and Nagowah, S. D. (2021). A predictive model to estimate effort in a sprint using machine learning techniques. International Journal of Information Technology, 13(3):02–10.
Rindell, K., Ruohonen, J., Holvitie, J., Hyrynsalmi, S., and Leppänen, V. (2021). Security in agile software sevelopment: A practitioner survey. Information and Software Technology, 131:106488.
Robles, B. D. V., Lara, I. L. A., Salgado, R. S., and Hidalgo-Reyes, M. (2023). Identification of methods, approaches, and factors in effort estimation for devops projects: A systematic literature mapping. In 2023 Mexican International Conference on Computer Science (ENC), pages 1–6. IEEE.
Rodríguez Sánchez, E., Vázquez Santacruz, E. F., and Cervantes Maceda, H. (2023). Effort and cost estimation using decision tree techniques and story points in agile software development. Mathematics, 11(6):1477.
Tawosi, V., Al-Subaihin, A., Moussa, R., and Sarro, F. (2022). A versatile dataset of agile open source software projects. In Proceedings of the 19th International Conference on Mining Software Repositories, pages 707–711.
Usman, M., Mendes, E., Weidt, F., and Britto, R. (2014). Effort estimation in agile software development: a systematic literature review. In Proceedings of the 10th international conference on predictive models in software engineering, PROMISE ’14, pages 82–91, New York, NY, USA. Association for Computing Machinery.
Van Solingen, R. and Berghout, E. W. (1999). The Goal/Question/Metric Method: a practical guide for quality improvement of software development. McGraw-Hill.
Publicado
04/11/2025
Como Citar
SANTOS, Marcos V.; SOARES, Michel S..
Cost Estimation for Agile Software Development in Small and Medium-Sized Enterprises. In: WORKSHOP DE TESES E DISSERTAÇÕES EM QUALIDADE DE SOFTWARE - SIMPÓSIO BRASILEIRO DE QUALIDADE DE SOFTWARE (SBQS), 24. , 2025, São José dos Campos/SP.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2025
.
p. 1-6.
DOI: https://doi.org/10.5753/sbqs_estendido.2025.13396.
