Development of a mathematical model for size estimation of Java Spring web applications using regression analysis
DOI:
https://doi.org/10.15587/1729-4061.2026.363077Keywords:
size estimation, normalization, nonlinear regression, outlier, Java, Spring, softwareAbstract
This study investigates the process to estimate the size of web applications developed in Java (country of origin – USA) using the Spring framework (country of origin – USA).
The task addressed is to improve reliability in estimating the size of the corresponding web applications. Estimating the size of web applications developed in Java using the Spring framework is an important task in software engineering. This makes it possible to assess the required time frame for implementing the functionality and to plan a project budget.
As a result of the work, a mathematical model was built for estimating the size of web applications in Java and Spring based on the normalizing transformation of the decimal logarithm; a corresponding program was developed to automate calculations. Quality parameters of the constructed model are as follows: R2 = 0.9173, MMRE = 0.1511, PRED(0.25) = 0.7931.
That has made it possible to improve the reliability of estimating the size of such web applications, namely, to reduce the value of average relative error and increase the level of prediction, as well as to narrow the widths of the confidence and prediction intervals.
A data set consisting of 36 projects was collected; its preprocessing was performed, which included checking for multivariate normality of the distribution and normalization by logarithmization. An appropriate nonlinear regression model was constructed. To improve the reliability of the model, an algorithm was applied that includes iterative removal of outliers using the square of the Mahalanobis distance and Fisher's criterion. A program was developed based on the constructed nonlinear regression model; the results were analyzed.
Analysis of the quality of the constructed model reveals its adequacy and applicability for solving tasks of estimating the size of the corresponding software
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Copyright (c) 2026 Lidiia Makarova, Liudmyla Latanska, Andrii Pukhalevych, Vladimir Kairov, Maksym Dzhurynksyi

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