(untitled) (Al-Farooq Journal of Sciences, 2026)
Software development has undergone a radical transformation with the emergence of AI-powered programming agents such as GitHub Copilot, Cursor, and Cloud Code. This shift has led to new challenges related to software repository governance and the ability to trace developer contributions. This research aims to analyze the concept of the "developer fingerprint" within this new context by examining the unique behavioral signatures left by both human developers and AI agents during the writing and modification of code. The research relies on analyzing a set of characteristics extracted from pull requests to develop a machine learning model capable of accurately identifying the source of code. Preliminary results have shown that AI agents possess distinct fingerprints, opening the door to a deeper understanding of human-machine collaboration patterns and providing a foundation for new software governance mechanisms.