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arXiv · 2604.06363

A Survey of Algorithm Debt in Machine and Deep Learning Systems: Definition, Smells, and Future Work

Emmanuel Iko-Ojo Simon·Chirath Hettiarachchi·Fatemeh Fard·Alex Potanin·Hanna Suominen
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Abstract

The adoption of Machine and Deep Learning (ML/DL) technologies introduces maintenance challenges, leading to Technical Debt (TD). Algorithm Debt (AD) is a TD type that impacts the performance and scalability of ML/DL systems. A review of 42 primary studies expanded AD's definition, uncovered its implicit presence, identified its smells, and highlighted future directions. These findings will guide an AD-focused study, enhancing the reliability of ML/DL systems.

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Emmanuel Iko-Ojo Simon, Chirath Hettiarachchi, Fatemeh Fard, Alex Potanin, Hanna Suominen. 2026-04-07. A Survey of Algorithm Debt in Machine and Deep Learning Systems: Definition, Smells, and Future Work. https://doi.org/10.1145/3806391

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