A Metrics-Oriented Architectural Model to Characterize Complexity on Machine Learning-Enabled Systems

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

Original language	English
Title of host publication	CAIN 2025
Subtitle of host publication	IEEE/ACM 4th International Conference on AI Engineering–Software Engineering for AI
Pages	256-260
Number of pages	4
ISBN (Electronic)	979-8-3315-0219-5
DOIs	https://doi.org/10.1109/CAIN66642.2025.00041
Publication status	Published - 27 Apr 2025

Keywords

@inproceedings{becc46a8744b4564a0264f0f80b5897a,

title = "A Metrics-Oriented Architectural Model to Characterize Complexity on Machine Learning-Enabled Systems",

keywords = "Software Metrics, Software Complexity, ML-Enabled Systems0, Machine Learning Engineering, MLOps",

author = "Ferreira, \{Renato Cordeiro\}",

year = "2025",

month = apr,

day = "27",

doi = "10.1109/CAIN66642.2025.00041",

language = "English",

isbn = "979-8-3315-0220-1",

pages = "256--260",

booktitle = "CAIN 2025",

}

TY - GEN

T1 - A Metrics-Oriented Architectural Model to Characterize Complexity on Machine Learning-Enabled Systems

AU - Ferreira, Renato Cordeiro

PY - 2025/4/27

Y1 - 2025/4/27

KW - Software Metrics

KW - Software Complexity

KW - ML-Enabled Systems0

KW - Machine Learning Engineering

KW - MLOps

UR - https://doi.org/10.1109/CAIN66642.2025.00041

U2 - 10.1109/CAIN66642.2025.00041

DO - 10.1109/CAIN66642.2025.00041

M3 - Conference contribution

SN - 979-8-3315-0220-1

SP - 256

EP - 260

BT - CAIN 2025

ER -