Design and implementation of online programming skill improvement system based on collaborative filtering algorithm

In response to the insufficiency of personalized learning support on online programming platforms, this paper designs and implements an online programming skill improvement system based on Spring Boot. The system adopts a front-end and back-end separation architecture, with the front end utilizing Vue.js and ECharts for data visualization. The back end is based on the Spring Boot microservices architecture, integrating technologies such as Dubbo and Nacos to achieve user management, problem management, and grading services. By analyzing users' historical answer records using collaborative filtering algorithms, the system generates personalized problem recommendation lists and creates user knowledge radar charts with ECharts to visually display learning progress and capability analysis. Test results indicate that the system's functional modules operate normally, with stable performance and secure user data protection. This system not only provides users with a personalized programming learning experience but also effectively enhances their programming skills, promoting the intelligent development of online programming education.