Work

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

Year: 2026

Type: article

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.

Source: ACM Computing Surveys

DOI: 10.1145/3806391

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

Institutions: Australian National University, University of British Columbia, University of Turku

Language: English

Topic: Software Engineering Research

Subfield: Information Systems

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

OpenAlex ID: W7148588649

FWCI: 9.077

Cites: 48

Cited by: 1

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