A Non-Intrusive Model for Capturing Metrics for Early Project Estimation in Agile Environments

• José Gamaliel Rivera Ibarra ITSON
• Gilberto Borrego ITSON
• Ramón René Palacio Cinco ITSON

DOI: https://doi.org/10.5753/cibse.2025.35339

Abstract

Early estimation is crucial in agile projects, but a lack of detailed initial requirements often makes it inaccurate. While data-driven models improve accuracy, the absence of company-specific databases hinders the reliance on historical data. This work presents a non-intrusive model for capturing key metrics (e.g., software size) in agile settings to facilitate building these databases. The model aims to support a hybrid estimation approach that combines data-driven techniques with expert judgment. Preliminary results highlight the need for automated metric capture to enhance the reliability of early agile estimations.

Keywords: agile development, effort estimation, software metrics

References

Alsaadi, B. and Saeedi, K. (2022). Data-driven effort estimation techniques of agile user stories: a systematic literature review. Artificial Intelligence Review, 55:5485–5516.

Barry, B. et al. (1981). Software engineering economics. New York, 197:40.

Beck, K., Beedle, M., van Bennekum, A., Cockburn, A., Cunningham, W., Fowler, M., Grenning, J., Highsmith, J., Hunt, A., Jeffries, R., Kern, J., Marick, B., Martin, R. C., Mellor, S., Schwaber, K., Sutherland, J., and Thomas, D. (2001). Manifesto for agile software development.

Rivera, J. G., Borrego, G., and Palacio, R. R. (2024). Early estimation in agile software development projects: A systematic mapping study. Informatics, 11.