A Meta-Summary of Challenges in Building Products with ML Components – Collecting Experiences from 4758+ Practitioners
A Meta-Summary of Challenges in Building Products with ML Components – Collecting Experiences from 4758+ Practitioners
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DOI：
10.1109/cain58948.2023.00034
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发表时间：
2023-03
期刊：
影响因子：
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通讯作者：
Nadia Nahar;Haoran Zhang;G. Lewis;Shurui Zhou;Christian Kästner
中科院分区：
文献类型：
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作者：
Nadia Nahar;Haoran Zhang;G. Lewis;Shurui Zhou;Christian Kästner
将机器学习(ML)组件融入软件产品带来了新的软件工程挑战，并加剧了现有的挑战。许多研究人员通过对实践者的采访和调查，投入了大量的精力来了解行业实践者在使用ML组件构建产品方面所面临的挑战。为了汇总和展示他们的集体发现，我们进行了一项元总结研究：我们收集了50篇相关论文，这些论文总共与4758名从业者互动，使用系统文献审查的指导方针。然后，我们收集、分组和组织了这些论文中提到的500多个挑战。我们强调了最常报告的挑战，并希望这一元摘要将成为研究界优先考虑这一领域的研究和教育的有用资源。
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.