3 papers
cs.SE2026
Quality Model for Machine Learning Components
Grace A. Lewis, Rachel Brower-Sinning, Robert Edman +5
Despite increased adoption and advances in machine learning (ML), there are studies showing that many ML prototypes do not reach the production stage and that testing is still larg…
cs.SE2025
Manifesto from Dagstuhl Perspectives Workshop 24452 -- Reframing Technical Debt
Paris Avgeriou, Ipek Ozkaya, Heiko Koziolek +2
This is the Dagstuhl Perspectives Workshop 24452 manifesto on Reframing Technical Debt. The manifesto begins with a one-page summary of Values, Beliefs, and Principles. It then ela…
cs.SE2024
A Synthesis of Green Architectural Tactics for ML-Enabled Systems
Heli Järvenpää, Patricia Lago, Justus Bogner +3
The rapid adoption of artificial intelligence (AI) and machine learning (ML) has generated growing interest in understanding their environmental impact and the challenges associate…