In Press Review Paper Uncorrected Proof

The following articles have been peer-reviewed and accepted for publication. They are scheduled to appear in an upcoming issue. These manuscripts are provided for early dissemination and may undergo minor copyediting and typesetting before final issue publication.

A predictive machine learning model for assessing software reusability :Review

Abstract

With the advancement of technology, the increasing size of software, and the need to develop it in record time and with less cost and effort, the need arose for a method to reuse software components and integrate them into other similar programs, Researchers have conducted reviews on the use of artificial intelligence, machine learning models

This review discusses the most important software metrics used as inputs in prediction models, . It also shows how machine learning techniques and artificial neural networks have been used instead of traditional statistical methods.

 This review highlights the challenges faced by researchers in this field.

How to Cite (In Press)

Luma Saoud, Safwan Omar Hasson (2026). A predictive machine learning model for assessing software reusability :Review. IRAQI JOURNAL OF STATISTICAL SCIENCES, In Press. https://doi.org/10.33899/iqjoss.v24i1.63574