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Updated: Jul 13, 2025

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The HoneyComb Paradigm for Research on Collective Human Behavior
Published on: January 19, 2019
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在使用更高层次网络中心性的软件开发过程中,定位社区的气味
Christoph Gote1,2,3, Vincenzo Perri2,3, Christian Zingg1
1Chair of Systems Design, ETH Zurich, Weinbergstrasse 56/58, 8092 Zurich, Switzerland.
概括
本研究引入了更高层次的网络模型,以检测软件开发过程中隐藏的社区气味,改善团队协作,并确定以前未知的问题,以更好地创建软件.
科学领域:
- 计算机科学 计算机科学
- 软件工程 软件工程 软件工程
- 网络分析 网络分析
背景情况:
- 社区的气味,如孤立和沟通不良,阻碍了软件开发团队的生产力.
- 现有的方法分析静态交互网络,未能在动态开发过程中精确定位气味.
- 高级网络模型为发现复杂的团队交互模式提供了更强大的方法.
研究的目的:
- 在软件开发中开发和验证用于检测社区气味的高级网络模型.
- 引入新的中心性措施,以确定团队互动网络中的有影响力的节点.
- 将这些方法应用于现实世界的软件开发团队,以识别和定位社区的气味.
主要方法:
- 开发了基于MOGen高阶网络模型的中心性措施.
- 通过使用五个经验数据集,验证了这些措施在预测有影响力的节点方面的有效性.
- 分析了genua GmbH的产品团队,在他们的开发过程中识别了特定的社区气味.
主要成果:
- 高级网络模型在团队开发过程中的两个领域成功识别了关键的社区气味.
- 团队知道一个已识别的社区气味,而第二个之前没有被识别.
- 新的高级网络中心性被证明可以有效地捕捉社区动态和间接关系.
结论:
- 高级网络模型为软件开发中识别和定位社区气味提供了强大的工具.
- 这种方法可以揭示隐藏的团队互动模式,并改善软件开发过程.
- 开发的中心性措施对社会网络分析领域做出了重大贡献,以了解社区动态.
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