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Abstract

This article explores a novel approach to evaluating developer performance and software quality by drawing parallels between programmers and football players. We highlight the inefficiencies in current assessment methods, which often rely on years of experience rather than quantitative metrics that truly reflect a developer's capabilities. By examining the historical evolution of both fields, we identify the significant advancements in performance analysis in football, which are rooted in statistical data. We propose a framework for developer analytics that utilizes performance metrics derived from programming contests, allowing for a more nuanced classification of programmers based on their skills and roles. Our findings suggest that adopting similar quantitative evaluation strategies in software development could enhance talent management, task allocation, and overall team productivity, ultimately driving progress in the industry.

Keywords

Developer analytics, Machine learning, Software quality, Performance evaluation, Programming contests, Football performance metrics

Article Type

Article

First Page

83

Last Page

94

Publication Date

4-30-2025

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