31 citations · 38 across the 5 of their papers we have counts for
3 papers · 1 filter
Capabilities for Better ML Engineering
Chenyang Yang, Rachel Brower-Sinning, Grace A. Lewis +2
In spite of machine learning's rapid growth, its engineering support is scattered in many forms, and tends to favor certain engineering stages, stakeholders, and evaluation prefere…
Aspirations and Practice of Model Documentation: Moving the Needle with Nudging and Traceability
Avinash Bhat, Austin Coursey, Grace Hu +5
The documentation practice for machine-learned (ML) models often falls short of established practices for traditional software, which impedes model accountability and inadvertently…
On Debugging the Performance of Configurable Software Systems: Developer Needs and Tailored Tool Support
Miguel Velez, Pooyan Jamshidi, Norbert Siegmund +2
Determining whether a configurable software system has a performance bug or it was misconfigured is often challenging. While there are numerous debugging techniques that can suppor…