Effort Estimation

Effort estimation in software development aims to accurately predict the time and resources needed for a project, crucial for effective planning and resource allocation. Current research heavily utilizes machine learning, particularly exploring various algorithms like neural networks (including deep learning models), support vector machines, and random forests, often applied to large datasets of project information. A key focus is improving the accuracy and reliability of these models, addressing challenges like variations in performance across different machine learning libraries and the limitations of current approaches in handling diverse data types and agile methodologies. These advancements have the potential to significantly improve project management and reduce cost overruns in software development.