The paper presents a systematic methodology for analyzing software developer productivity by refining contribution rate metrics to distinguish meaningful development efforts from anomalies. Using the Mean-High Model Contribution Rate (mhMCR) method, the research introduces a statistical framework that focuses on continuous contributions, mitigating distortions caused by tool-assisted refactoring, delayed commits, or automated changes. The methodology integrates clustering techniques, commit time deltas, and contribution sizes to isolate natural, logical work patterns and supports the accurate imputation of effort for contributions outside these patterns. Through empirical validation across multiple commercial repositories, the mhMCR method demonstrates enhanced precision in productivity measurement in identifying sustained developer activity. The findings provide actionable insights for optimizing team performance and workflow management in modern software engineering practices.
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