Analysis of Risk Factors in Global Software Development: A Cross-Continental Study Using Modified Firefly Algorithm

Citation

Iftikhar, Asim and Ali, Syed Mubashir and Alam, Muhammad Mansoor and Musa, Shahrulniza and Mohd Su'ud, Mazliham (2022) Analysis of Risk Factors in Global Software Development: A Cross-Continental Study Using Modified Firefly Algorithm. Computational Intelligence and Neuroscience, 2022. pp. 1-13. ISSN 1687-5265

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Abstract

In today’s competitive world, software organizations are moving towards global software development (GSD). This became even more significant in times such as COVID-19 pandemic, where team members residing in different geographical locations and from different cultures had to work from home to carry on their tasks and responsibilities as travelling was restricted. These teams are distributed in nature and work on the same set of goals and objectives. Some of the key challenges which software practitioners face in GSD environment are cultural differences, communication issues, use of different software models, temporal and spatial distance, and risk factors. Risks can be considered as a biggest challenge of other challenges, but not many researchers have addressed risks related to time, cost, and resources. In this research paper, a comprehensive analysis of software project risk factors in GSD environment has been performed. Based on the literature review, 54 risk factors were identified in the context of software development. These were further classified by practitioners into three dimensions, i.e., time, cost, and resource. A Pareto analysis has been performed to discover the most important risk factors, which could have bad impact on software projects. Furthermore, a modified firefly algorithm has been designed and implemented to evaluate and prioritize the pertinent risk factors obtained after the Pareto analysis. All important risks have been prioritized according to the fitness values of individual risks. The top three risks are “failure to provide resources,” “cultural differences of participants,” and “inadequately trained development team members.”

Item Type: Article
Uncontrolled Keywords: Algorithms
Subjects: Q Science > QA Mathematics > QA71-90 Instruments and machines > QA75.5-76.95 Electronic computers. Computer science
Divisions: Faculty of Computing and Informatics (FCI)
Depositing User: Ms Nurul Iqtiani Ahmad
Date Deposited: 01 Aug 2022 00:36
Last Modified: 01 Aug 2022 00:36
URII: http://shdl.mmu.edu.my/id/eprint/10249

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