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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 15 Issue 7, 2024.
Abstract: To create products that are both cost effective and high quality, a majority of software development companies are following the principles of global software development, or GSD. One of the most significant and challenging stages of the agile software development process is requirements change management (RCM); however, the execution of agile software development activities is hindered by the geographical distance between the GSD teams, especially when it comes to agile requirements change management (ARCM). The literature claims that, in a particular context, ARCM can profit from applying Multi-Criteria Decision-Making (MCDM) techniques. Within the area of ARCM, an optimal framework can be offered constitutionally, thus presenting an effective decision-making process that ought to encourage higher consumer satisfaction with software projects created in such a way. A methodology for applying the MCDM method in the ARCM context is presented in this paper. In particular, we propose a model for investigating the prioritization of ARCM success factors in the GSD context based on a decision-making method; namely, the Best-Worst Method (BWM). The BWM’s ability to solve intricate decision-making problems with multiple criteria and alternatives is demonstrated by the proposed model’s findings.
Abdulmajeed Aljuhani. “Identification of Agile Requirements Change Management Success Factors in Global Software Development Based on the Best-Worst Method”. International Journal of Advanced Computer Science and Applications (IJACSA) 15.7 (2024). http://dx.doi.org/10.14569/IJACSA.2024.01507131
@article{Aljuhani2024,
title = {Identification of Agile Requirements Change Management Success Factors in Global Software Development Based on the Best-Worst Method},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2024.01507131},
url = {http://dx.doi.org/10.14569/IJACSA.2024.01507131},
year = {2024},
publisher = {The Science and Information Organization},
volume = {15},
number = {7},
author = {Abdulmajeed Aljuhani}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.