Now showing items 1-4 of 4
A genetic algorithm based framework for software effort prediction
Background: Several prediction models have been proposed in the literature using different techniques obtaining different results in different contexts. The need for accurate effort predictions for projects is one of the ...
An empirical evaluation of NASA-MDP data sets using a genetic defect-proneness prediction framework
In software engineering, software quality is an important research area. Automated generation of learning schemes plays an important role and represents an efficient way to detect defects in software projects, thus ...
An Empirical Validation of an Automated Genetic Software Effort Prediction Framework Using the ISBSG Dataset
The complexity of providing accurate software effort prediction models is well known in the software industry. Several prediction models have been proposed in the literature using different techniques, with different ...
COSMIC Base Functional Components in Functional Size Based Effort Estimation Models
Software effort estimation models has been an area of considerable research for many years and it is still a challenge for software engineering. Although Functional Size Measurement (FSM) methods have become widely used, ...