Decoding Code Quality: A Software Metric Analysis of Open-Source JavaScript Projects

The popularity of web-based solutions has seen rapid growth in the last decade, which has raised the demand for JavaScript (JS) usage in personal projects and enterprise solutions. While the extensive demand for JS has elevated, studies have yet to be done on how JS development follows the rules and guides for writing code to meet quality standards. Consequently, we choose to investigate the practice of JS on different project sizes, the developers’ experience, and their impact on code quality and development. To achieve this goal, we perform the code quality analysis of 200 open-source JS projects from GitHub on 10 code quality metrics. We design our research study to examine the influence of project size on issue density, find relationships among 10 code metrics, how code quality changes with developer experience, and determine the capabilities of existing source code evaluation tools. Our findings reveal that issue density decreases with increasing developer experience and project size. In addition, our quantitative study suggests that with the increase in project size and line of code (LOC), project maintainability decreases, leading to more issues such as errors, complexity, code smell, and duplication. However, as developers become more experienced, they face fewer coding challenges, enhance code quality, and reduce code smell per line of code (LOC). Our study also offers valuable insights into the capabilities of the 6 tools mentioned above to advance code evaluation practices.