Software effort estimation by tuning COOCMO model parameters using differential evolution

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{Aljahdali:2010:AICCSA,

• author = "Sultan Aljahdali and Alaa F. Sheta",
• title = "Software effort estimation by tuning COOCMO model parameters using differential evolution",
• booktitle = "2010 IEEE/ACS International Conference on Computer Systems and Applications (AICCSA)",
• year = "2010",
• month = "16-19 " # may,
• address = "Hammamet, Tunisia",
• abstract = "Accurate estimation of software projects costs represents a challenge for many government organisations such as the Department of Defense (DOD) and NASA. Statistical models considerably used to assist in such a computation. There is still an urgent need on finding a mathematical model which can provide an accurate relationship between the software project effort/cost and the cost drivers. A powerful algorithm which can optimise such a relationship via tuning mathematical model parameters is urgently needed. In two new model structures to estimate the effort required for software projects using Genetic Algorithms (GAs) were proposed as a modification to the famous Constructive Cost Model (COCOMO). In this paper, we follow up on our previous work and present Differential Evolution (DE) as an alternative technique to estimate the COCOMO model parameters. The performance of the developed models were tested on NASA software project dataset provided in. The developed COCOMO-DE model was able to provide good estimation capabilities.",
• keywords = "genetic algorithms, genetic programming, sbse, COOCMO model parameter tuning, NASA software project dataset, constructive cost model, differential evolution, mathematical model, optimisation algorithm, software effort estimation, software projects cost estimation, statistical model, optimisation, software cost estimation",
• DOI = "doi:10.1109/AICCSA.2010.5586985",
• notes = "'We suggest the use of Genetic Programming (GP) technique to build suitable model structure for the software effort estimation.' Also known as \cite{5586985}",

}

Genetic Programming entries for Sultan Aljahdali Alaa Sheta

Citations