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.