THE NON-LINEAR REGRESSION MODEL TO ESTIMATE THE SOFTWARE SIZE OF OPEN SOURCE JAVA-BASED SYSTEMS
Natalia Prykhodko, Sergiy B. Prykhodko · Radio Electronics Computer Science Control · 2018
Context. The problem of estimating the software size in the early stage of a software project is important, since the informationobtained from estimating the software size is used for predicting the software development effort, including open-source Java-basedinformation systems. The object of the study is the process of estimating the software size of open-source Java-based informationsystems. The subject of the study is the regression models for estimating the software size of open-source Java-based informationsystems.Objective. The goal of the work is the creation of the non-linear regression model for estimating the software size of open-sourceJava-based information systems on the basis of the Johnson multivariate normalizing transformation.Method. The model, confidence and prediction intervals of multiply non-linear regression for estimating the software size ofopen-source Java-based information systems are constructed on the basis of the Johnson multivariate normalizing transformation fornon-Gaussian data with the help of appropriate techniques. The techniques to build the models, equations, confidence and predictionintervals of non-linear regressions are based on the multiple non-linear regression analysis using the multivariate normalizingtransformations. The appropriate techniques are considered. The techniques allow to take into account the correlation betweenrandom variables in the case of normalization of multivariate non-Gaussian data. In general, this leads to a reduction of the meanmagnitude of relative error, the widths of the confidence and prediction intervals in comparison with the linear models or nonlinearmodels constructed using univariate normalizing transformations.Results. Comparison of the constructed model with the linear model and non-linear regression models based on the decimallogarithm and the Johnson univariate transformation has been performed.Conclusions. The non-linear regression model to estimate the software size of open-source Java-based information systems isconstructed on the basis of the Johnson multivariate transformation for SB family. This model, in comparison with other regressionmodels (both linear and non-linear), has a larger multiple coefficient of determination, a larger value of percentage of prediction anda smaller value of the mean magnitude of relative error. The prospects for further research may include the application of othermultivariate normalizing transformations and data sets to construct the non-linear regression model for estimating the software sizeof open-source Java-based information systems.