Enabling GSD Task Allocation via Cloud-based Software Processes

Sami Alajrami, B. Gallina, A. Romanovsky
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引用次数: 3

Abstract

Allocating tasks to distributed sites in Global Software Development (GSD) projects is often done unsystematically and based on the personal experience of project managers. Wrong allocation decisions increase the project’s risks as tasks have dependencies that are inherited by the distributed sites. Decision support can help make the task allocation a more informed and systematic process. The challenges in allocating tasks to distributed sites exist because of three distance dimensions between sites (geographical, temporal and cultural). An informed task allocation decision needs to consider these distances. Therefore, in this paper, we propose to integrate and semi-automate the calculation of an existing Global Distance Metric (GDM) into an architecture that supports executing cloud-based software processes. We analyze the potential of integrating the GDM into this architecture and identify the needed extensions to the architecture.
通过基于云的软件进程实现GSD任务分配
在Global Software Development (GSD)项目中,将任务分配给分布式站点通常是基于项目经理的个人经验而非系统地完成的。错误的分配决策增加了项目的风险,因为任务具有由分布式站点继承的依赖关系。决策支持有助于使任务分配成为一个更加明智和系统的过程。将任务分配给分布式站点存在挑战,因为站点之间存在三个距离维度(地理、时间和文化)。明智的任务分配决策需要考虑这些距离。因此,在本文中,我们建议将现有的全球距离度量(GDM)的计算集成和半自动化到一个支持执行基于云的软件过程的架构中。我们分析了将GDM集成到该体系结构中的可能性,并确定了该体系结构所需的扩展。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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