Practical Implementation and Analysis of Software Metrics Impact on Maintainability in Open-Source Systems
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Abstract
Common software metrics and maintainability measures in open-source Java are examined in this research.The authors test the major object-oriented metrics—Coupling Between Objects (CBO), Lines of Code (LOC), Weighted Methods per Class (WMC), Lack of Cohesion of Methods (LCOM), Depth of Inheritance Tree (DIT), and Cyclomatic Complexity—against real-world maintainability indicators like bug counts, code modifications, and developer turnover. The authors use Python data analysis and visualization to find statistically significant patterns in Spearman correlation analysis.
The findings indicate that metrics such as CBO and cyclomatic complexity are very predictive in terms of maintenance effort, whereas others, such as DIT, provide little insight. In addition to theoretical justification, this work provides a practical, reproducible workflow to be implemented by software engineers to give priority to code quality and make more intelligent maintenance decisions. Finally, this study ties the strengths of academic measures and the real-world aspects of daily software engineering.
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