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Title: A Meta-Summary of Challenges in Building Products with ML Components – Collecting Experiences from 4758+ Practitioners
Incorporating machine learning (ML) components into software products raises new software-engineering challenges and exacerbates existing ones. Many researchers have invested significant effort in understanding the challenges of industry practitioners working on building products with ML components, through interviews and surveys with practitioners. With the intention to aggregate and present their collective findings, we conduct a meta-summary study: We collect 50 relevant papers that together interacted with over 4758 practitioners using guidelines for systematic literature reviews. We then collected, grouped, and organized the over 500 mentions of challenges within those papers. We highlight the most commonly reported challenges and hope this meta-summary will be a useful resource for the research community to prioritize research and education in this field.  more » « less
Award ID(s):
2131477
NSF-PAR ID:
10444830
Author(s) / Creator(s):
; ; ; ;
Date Published:
Journal Name:
2023 IEEE/ACM 2nd International Conference on AI Engineering – Software Engineering for AI (CAIN)
Page Range / eLocation ID:
171 to 183
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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