Uncovering Determinants of Code Quality in Education via Static Code Analysis

Abstract

The role of static code analysis in enhancing the quality of software codes is widely acknowledged. Static code analysis facilitates the examination of code for irregularities without program execution, which significantly impacts project quality. Furthermore, tools for static code analysis serve as educational aids, imparting essential lessons on coding practices. Motivated by the growing complexity of software projects and the pivotal role of code quality in academic performance within computing disciplines, this research examines over 500 student projects using static code analysis tools. The aim is to determine metrics that influence the code quality of student projects. The study investigates how metrics, such as project setup, influence code quality and students’ academic performances. By adopting a broad approach, the investigation determines the overall impact of these metrics on the technical integrity of software engineering projects and academic outcomes. Insights derived from this study are anticipated to enhance teaching strategies and curriculum development, aiming to improve academic performance by promoting better code quality.

Keywords

• Academic performance
• code quality
• education
• educational practices
• static code analysis