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

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Date

2026-04-27

Authors

Simon, Emmanuel
Hettiarachchi, Chirath
Fard, Fatemeh
Potanin, Alex
Suominen, Hanna

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Research Projects

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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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Keywords

algorithm debt, deep learning, machine learning, software quality, systematic literature review, Technical debt

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https://hdl.handle.net/1885/733811171

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ANU Research Publications

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ACM Computing Surveys

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Journal article

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Publication

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DOI

10.1145/3806391

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