L. E. G. Martins

Artificial Intelligence Techniques to Enhance Cost, Effort, and Schedule Estimates in Software Development Projects: A Systematic Literature Review

The findings indicate that techniques such as artificial neural networks, optimization algorithms, machine learning models, and hybrid approaches consistently yield improvements in estimation accuracy, with average error reductions reported in the literature ranging approximately from 15% to 30% when compared with traditional methods.