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全球化软件开发中的风险因素分析:基于改进萤火虫算法的跨大陆研究。

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

机构信息

College of Computer Science & Info. Sys, Institute of Business Management (IoBM), Korangi Creek, Karachi, Pakistan.

Malaysian Institute of Information Technology, Universiti Kuala Lumpur, (UniKL MIIT), Kuala Lumpur, Malaysia.

出版信息

Comput Intell Neurosci. 2022 Jun 6;2022:4936748. doi: 10.1155/2022/4936748. eCollection 2022.

DOI:10.1155/2022/4936748
PMID:35707203
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9192222/
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."

摘要

在当今竞争激烈的世界中,软件组织正在向全球软件开发(GSD)转移。在 COVID-19 大流行等时期,这种情况变得更加重要,因为团队成员居住在不同的地理位置和文化背景中,必须在家工作,以继续履行其任务和职责,因为旅行受到限制。这些团队是分布式的,致力于实现相同的目标和目的。软件从业者在 GSD 环境中面临的一些关键挑战包括文化差异、沟通问题、使用不同的软件模型、时间和空间距离以及风险因素。风险可以被认为是其他挑战的最大挑战,但没有多少研究人员解决与时间、成本和资源相关的风险。在本研究论文中,对 GSD 环境中的软件项目风险因素进行了全面分析。基于文献综述,在软件开发背景下确定了 54 个风险因素。这些因素进一步由从业者分为时间、成本和资源三个维度。进行了帕累托分析,以发现可能对软件项目产生不利影响的最重要风险因素。此外,设计并实现了一种改进的萤火虫算法,以评估和确定帕累托分析后获得的相关风险因素的优先级。根据各个风险的适应度值对所有重要风险进行了优先级排序。排名前三的风险是“未能提供资源”、“参与者的文化差异”和“开发团队成员培训不足”。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0006/9192222/20d7d62308ee/CIN2022-4936748.006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0006/9192222/de9fc9b6788e/CIN2022-4936748.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0006/9192222/ddb9f02e7d56/CIN2022-4936748.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0006/9192222/5e6a5801dd06/CIN2022-4936748.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0006/9192222/2ebc94597c3f/CIN2022-4936748.004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0006/9192222/4987fb211881/CIN2022-4936748.005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0006/9192222/20d7d62308ee/CIN2022-4936748.006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0006/9192222/de9fc9b6788e/CIN2022-4936748.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0006/9192222/ddb9f02e7d56/CIN2022-4936748.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0006/9192222/5e6a5801dd06/CIN2022-4936748.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0006/9192222/2ebc94597c3f/CIN2022-4936748.004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0006/9192222/4987fb211881/CIN2022-4936748.005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0006/9192222/20d7d62308ee/CIN2022-4936748.006.jpg

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本文引用的文献

1
Risk Prediction by Using Artificial Neural Network in Global Software Development.利用人工神经网络进行全球软件开发的风险预测。
Comput Intell Neurosci. 2021 Dec 9;2021:2922728. doi: 10.1155/2021/2922728. eCollection 2021.