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cs.SE2026
Architecturally Significant MLOps Guidelines for ML Model Integration and Deployment: a Gray Literature Review
Faezeh Amou Najafabad, Markus Haug, Keerthiga Rajenthiram +2
Context. Despite the growing adoption of Machine Learning Operations (MLOps), teams often approach MLOps projects in an ad hoc manner due to the lack of consolidated architectural…
cs.SE2026
Exploring CoCo Challenges in ML Engineering Teams: Insights From the Semiconductor Industry
A. Azamnouri, M. Haug, L. Woltmann +3
The integration of machine learning (ML) into complex software systems has increased challenges in collaboration and communication (CoCo) of the teams building these systems. ML en…