28 citations · 28 across the 4 of their papers we have counts for
4 papers
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…
Defining a Reference Architecture for Edge Systems in Highly-Uncertain Environments
Kevin Pitstick, Marc Novakouski, Grace A. Lewis +1
Increasing rate of progress in hardware and artificial intelligence (AI) solutions is enabling a range of software systems to be deployed closer to their users, increasing applicat…
Using Quality Attribute Scenarios for ML Model Test Case Generation
Rachel Brower-Sinning, Grace A. Lewis, Sebastían Echeverría +1
Testing of machine learning (ML) models is a known challenge identified by researchers and practitioners alike. Unfortunately, current practice for ML model testing prioritizes tes…
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…