Abstract

With the ongoing development of software engineering and programming education, the demand for evaluating programming code quality is increasing. High-quality code not only en-hances software maintainability and performance but also helps developers and learners optimize their coding skills. This paper focuses on the design and implementation of an evaluation system for computer programming code quality, proposing a multi-dimensional evaluation method that includes readability, complexity, efficiency, and security. The system combines static analysis with machine learning to automate code analysis and optimization recommendations, providing users with objective feedback on code quality. Additionally, this paper explores application cases of the system in programming education and software development, demonstrating its effectiveness in improving code quality and enhancing users' programming skills. Finally, the research contribu-tions are summarized, and directions for future improvements are proposed to further enhance the system’s intelligence and applicability.

Keywords: 

code quality, code evaluation system, static analysis, machine learning, programming education

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