Leveraging AI for Enhanced Software Effort Estimation: A Comprehensive Study and Framework Proposal
It addresses software project planning and resource allocation, but appears incremental as it reviews existing methods without introducing a new paradigm.
This paper tackles the problem of software effort estimation by applying AI techniques to improve accuracy and reliability, identifying the most effective machine learning models through performance evaluation.
This paper presents an extensive study on the application of AI techniques for software effort estimation in the past five years from 2017 to 2023. By overcoming the limitations of traditional methods, the study aims to improve accuracy and reliability. Through performance evaluation and comparison with diverse Machine Learning models, including Artificial Neural Network (ANN), Support Vector Machine (SVM), Linear Regression, Random Forest and other techniques, the most effective method is identified. The proposed AI-based framework holds the potential to enhance project planning and resource allocation, contributing to the research area of software project effort estimation.