A Survey of Algorithm Debt in Machine and Deep Learning Systems: Definition, Smells, and Future Work
Software Engineering
2026-04-09 v1
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.
Cite
@article{arxiv.2604.06363,
title = {A Survey of Algorithm Debt in Machine and Deep Learning Systems: Definition, Smells, and Future Work},
author = {Emmanuel Iko-Ojo Simon and Chirath Hettiarachchi and Fatemeh Fard and Alex Potanin and Hanna Suominen},
journal= {arXiv preprint arXiv:2604.06363},
year = {2026}
}
Comments
ACM Computing Surveys