"A Multidimensional Static Code Analysis Dataset for Assessing Software Quality, Complexity, and Maintainability"

"Software systems are increasingly complex and massive in the modern era. Quantitative approaches are necessary to evaluate the quality of the code, maintainability, and security of the software system. This research proposes and characterizes a structured dataset built from static code analysis with 405 source code files and 41 software metrics. The proposed dataset is a multidimensional data set with various measurement dimensions: size-related metrics, software complexity measures, quality violation measures, documentation density measures, and security-related measures. The proposed dataset is a combination of traditional software science metrics and maintainability and defect-related metrics. The proposed dataset is heterogeneous in nature with high-variance modules and is more suitable for statistical modeling and machine learning approaches to predict defects and assess the maintainability of the software system. The proposed dataset is useful in exploring the relationship between the structure of the code and the quality of the software system."