31 citations · 60 across the 7 of their papers we have counts for
5 papers · 1 filter
The Product Beyond the Model -- An Empirical Study of Repositories of Open-Source ML Products
Nadia Nahar, Haoran Zhang, Grace Lewis +2
Machine learning (ML) components are increasingly incorporated into software products for end-users, but developers face challenges in transitioning from ML prototypes to products.…
A Meta-Summary of Challenges in Building Products with ML Components -- Collecting Experiences from 4758+ Practitioners
Nadia Nahar, Haoran Zhang, Grace Lewis +2
Incorporating machine learning (ML) components into software products raises new software-engineering challenges and exacerbates existing challenges. Many researchers have invested…
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…
Collaboration Challenges in Building ML-Enabled Systems: Communication, Documentation, Engineering, and Process
Nadia Nahar, Shurui Zhou, Grace Lewis +1
The introduction of machine learning (ML) components in software projects has created the need for software engineers to collaborate with data scientists and other specialists. Whi…
SysMap: A Lightweight Software Visualization Tool to Analyze the Software Evolution of a System
Fazle Rabbi, Nishat Tasnim Niloy, Nadia Nahar +1
Software visualization helps to comprehend the system by providing a vivid illustration. The developers, as well as the analysts, can have a glance over the total system to underst…