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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TP31; TN915.09

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    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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  • Received:
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  • Online: September 23,2017
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