基于大数据的GitHub开源社区开源项目量化分析
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1.上海大学通信与信息工程学院 上海 200000; 2.中科院上海高等研究院智慧城市研究中心 上海 201210

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TP31; TN915.09

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Quantitative analysis of open source project in GitHub community based on big data
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1.School of Communication and information engineering, Shanghai University, Shanghai 200000, China; 2. Smart City Research Center, Shanghai Advanced Research Institute, Chinese Academy of Science, Shanghai 201210,China

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    摘要:

    通过挖掘GitHub开源项目开发过程中的数据,基于复杂网络和机器学习算法,量化分析出软件开发团队当前进展的相关指标。利用网络爬虫抓取项目数据进行复杂网络的相关分析,结果显示GitHub开源社区中的开发者网络具有小世界效应,一些项目的开发者网络具有无标度网络效应,网络聚集系数随着项目的新生会出现峰值随后趋于正常,并展示了基于时间序列的网络模块度以及其他表征网络特性指标的变化趋势。量化分析结果使管理者能够动态详实的掌握开发团队的情况,合理分配资源、安排开发任务,提高软件开发效率。

    Abstract:

    By mining the data on GitHub open source project’s developing progress, based on the complex network theory and machine learning, the paper analyses the relative index in the current progress of software developing group with quantitative way. The research uses data which acquire by internet worm from open source software(OSS) in GitHub to analysis with complex networks. The results show that the network of OSS developer has a small world effect, some of the project developer network has scalefree network effect, the clustering coefficient of the network will has a peak value with the new project then tend to be normal. The paper also shows the change of network modularity and other characteristics of network based on time series. Quantitative analysis results can enable the managers to acknowledge the situation of developing group dynamically so well that they can be reasonable to allocate the resource ,to arrange the developing task and to improve its efficiency.

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叶培根,毛建华,刘学锋.基于大数据的GitHub开源社区开源项目量化分析[J].电子测量技术,2017,40(8):84-89

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  • 在线发布日期: 2017-09-23
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