Software Effort Estimation from Use Case Diagrams Using Nonlinear Regression Analysis
This addresses the problem of accurate effort estimation for project managers in software development, but it is incremental as it builds on existing regression methods with a size-based adaptation.
The researchers tackled software effort estimation in early project stages by proposing a new model using nonlinear regression analysis on use case diagrams, concluding that a single equation is insufficient for varying software sizes and developing three equations to handle different size ranges.
Software effort estimation in the early stages of the software life cycle is one of the most essential and daunting tasks for project managers. In this research, a new model based on non-linear regression analysis is proposed to predict software effort from use case diagrams. It is concluded that, where software size is classified from small to very large, one linear or non-linear equation for effort estimation cannot be applied. Our model with three different non-linear regression equations can incorporate the different ranges in software size.