A genetic algorithm based framework for software effort prediction

Tipo de publicación: Journal Article

Publicado en: Journal of Software Engineering Research and Development

Autores
  • Murillo-morera, Juan
  • Quesada-López, Christian
  • Castro-Herrera, Carlos
  • Jenkins, Marcelo

Investigadores del CITIC asociados a la publicación
Juan de Dios Murillo Morera
Christian Quesada-López
Carlos Castro Herrera
Marcelo Jenkins Coronas

Proyecto asociado a la publicación
Medición automatizada del tamaño funcional para aplicaciones de software transaccionales

Palabras claves
  • Effort prediction model
  • Empirical study
  • function points
  • Genetic approach
  • ISBSG dataset
  • Learning schemes
  • Machine learning
  • Software effort estimation
Resumen

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 most critical and complex issues in the software industry. The automated selection and the combination of techniques in alternative ways could improve the overall accuracy of the prediction models.

DOI BIBTEXT

Datos bibliográficos
Cita bibliográfica
A genetic algorithm based framework for software effort prediction