Genetic Programming as Alternative for Predicting Development Effort of Individual Software Projects

被引：6
|
作者：
Chavoya, Arturo [1 ]
Lopez-Martin, Cuauhtemoc [1 ]
Andalon-Garcia, Irma R. [1 ]
Meda-Campana, M. E. [1 ]
机构：
[1] Univ Guadalajara, Dept Informat Syst, CUCEA, Zapopan, Jalisco, Mexico
来源：
PLOS ONE | 2012年 / 7卷 / 11期
关键词：
COST ESTIMATION;
D O I：
10.1371/journal.pone.0050531
中图分类号：
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号：
07 ; 0710 ; 09 ;
摘要：
Statistical and genetic programming techniques have been used to predict the software development effort of large software projects. In this paper, a genetic programming model was used for predicting the effort required in individually developed projects. Accuracy obtained from a genetic programming model was compared against one generated from the application of a statistical regression model. A sample of 219 projects developed by 71 practitioners was used for generating the two models, whereas another sample of 130 projects developed by 38 practitioners was used for validating them. The models used two kinds of lines of code as well as programming language experience as independent variables. Accuracy results from the model obtained with genetic programming suggest that it could be used to predict the software development effort of individual projects when these projects have been developed in a disciplined manner within a development-controlled environment.
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页数：10
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