Design of software effort estimation models an approach based on linear genetic programming

Created by W.Langdon from gp-bibliography.bib Revision:1.7630

@InProceedings{Sanchez:2017:CLEI,

• author = "Roberto Sanchez and Diego P. Pinto-Roa",
• booktitle = "2017 XLIII Latin American Computer Conference (CLEI)",
• title = "Design of software effort estimation models an approach based on linear genetic programming",
• year = "2017",
• month = sep,
• keywords = "genetic algorithms, genetic programming, SBSE, Software Effort Estimation, COCOMO, Linear Genetic Programming",
• DOI = "doi:10.1109/CLEI.2017.8226469",
• abstract = "Estimating effort is a very important task in any organization. Significant over or under-estimates can be very expensive for software project companies. The use of computing intelligence methods has been recently proposed for software development effort estimation. In this study, we present new models to estimate the effort required for the development of software projects. These new models were calculated using Linear Genetic Programming (PGL). The results show that the proposed models get more precise and more effective estimation for Mean Magnitude Relative error (MMRE) and Mean Magnitude of Relative Error relative to the Estimate (MMER) than using the constructive cost model (COCOMO). We performed the study based on three stages according to the type of project. The models were designed and validated by simulation with the public repository dataset COCOMO81 and NASA93. Performance of the proposed models EE_PGLa, EE_PGLb and EE_PGLc are more accurate than COCOMO.",
• notes = "In spanish? Programacion Genetica Lineal

  Also known as \cite{8226469}",

}

Genetic Programming entries for Roberto Sanchez Diego P Pinto-Roa

Citations