A Hybrid Model for Improving Software Cost Estimation in Global Software Development

作     者：Mehmood Ahmed Noraini B.Ibrahim Wasif Nisar Adeel Ahmed Muhammad Junaid Emmanuel Soriano Flores Divya Anand 

作者机构：Faculty of Computer Science and Information TechnologyUniversiti Tun Hussein Onn Malaysia Parit RajaBatu Pahat86400Malaysia Department of Computer ScienceCOMSATS University Wah Cantt CampusIslamabad47010Pakistan Department of Information TechnologyThe University of HaripurKhyber Pakhtunkhwa22620Pakistan Engineering Research Innovation GroupUniversidad Europea del AtlanticoSantander39011Spain 

出 版 物：《Computers, Materials & Continua》 (计算机、材料和连续体（英文）)

年 卷 期：2024年第78卷第1期

页      面：1399-1422页

核心收录：

学科分类：08[工学] 0835[工学-软件工程] 081202[工学-计算机软件与理论] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：We would like to take this opportunity to express our gratitude to all those who made a contribution to the completion of this article 

主　　题：Artificial neural networks COCOMO II cost drivers global software development linear regression software cost estimation 

摘      要：Accurate software cost estimation in Global Software Development(GSD)remains challenging due to reliance on historical data and expert *** models,such as the Constructive Cost Model(COCOMO II),rely heavily on historical and accurate *** addition,expert judgment is required to set many input parameters,which can introduce subjectivity and variability in the estimation ***,there is a need to improve the current GSD models to mitigate reliance on historical data,subjectivity in expert judgment,inadequate consideration of GSD-based cost drivers and limited integration of modern technologies with cost *** study introduces a novel hybrid model that synergizes the COCOMO II with Artificial Neural Networks(ANN)to address these *** proposed hybrid model integrates additional GSD-based cost drivers identified through a systematic literature review and further vetted by industry *** article compares the effectiveness of the proposedmodelwith state-of-the-artmachine learning-basedmodels for software cost *** the NASA 93 dataset by adopting twenty-six GSD-based cost drivers reveals that our hybrid model achieves superior accuracy,outperforming existing *** findings indicate the potential of combining COCOMO II,ANN,and additional GSD-based cost drivers to transform cost estimation in GSD.