基于存储库数据挖掘的开源软件成功度量方法

开源软件已广泛应用于各软件领域，例如操作系统、容器等，但目前尚没有一种能够综合度量开源软件的方法.我们在用户兴趣度量和开发参与度量的基础上，提出了一种能够克服度量维度单一的局限性的度量方法.基于DM模型、软件生存力模型等相关文献研究和开源软件存储库数据挖掘，通过对项目过程数据进行聚类、主成分分析、回归分析和对开发过程的思考，本文提出一种基于存储库数据和统计学算法的开源软件成功度度量模型.并通过与用户兴趣度量结果和开发参与度量结果对比分析，证明本文的度量模型能够基于可自动无扰采集的存储库数据，更全面的衡量开源软件项目的成功.度量模型可应用于企业选择优质开源项目、学术研究、智能项目推荐等领域.

Open Source Software Success Measurement Method Based on Mining Software Repository

The open source software (OSS) is widely used in various software fields,such as operating system,container,etc.But there is no method to measure open source software comprehensively.Based on the measurement of user interest and the development of participation metrics,we propose a method that can overcome the single limitation of the metric dimension.Based on DM model,software viability model and other relevant literature research,mining of software repository,we consider the OSS development process and propose an OSS success evaluation model through clustering,principal component analysis and regression analysis.By comparing the metric score of user interest method and development participation method,the evaluation model can be used to measure the success of OSS projects based on the data collected automatically without interference.The evaluation model can be applied to select high quality open source projects,academic research,intelligent project recommendation,etc.