Maintenance Efforts Improvements in the New Software Generation Languages Using ISBSG Dataset: Benchmarking
Kenza Meridji, Khalid T. Al‐Sarayreh · 2025
to determine which features have the main effect on enhancement effort based on language type and their relationship, this paper presents an exploratory study that uses two data analysis techniques: statistical analysis and feature selection using ANOVA on selected projects from the ISBSG R12 dataset that use 3GL and 4GL languages in enhancement. Regarding this, the study used two methodologies: Python correlation analysis and Excel sheet analysis. To varying degrees, the statistical analysis indicated that the factors that were chosen were significant. To determine which features are crucial for predicting enhancement effort, ANOVA was employed. A significant correlation was found between the most dependent and independent parameters that affect the effort put into improving each language type, according to the statistical analysis. ANOVA exposed those characteristics.