How Do Engineers Perceive Difficulties in Engineering of Machine-Learning Systems? - Questionnaire Survey
How Do Engineers Perceive Difficulties in Engineering of Machine-Learning Systems? - Questionnaire Survey
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DOI：
10.1109/cesser-ip.2019.00009
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发表时间：
2019-05
期刊：
影响因子：
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通讯作者：
F. Ishikawa;Nobukazu Yoshioka
中科院分区：
文献类型：
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作者：
F. Ishikawa;Nobukazu Yoshioka
近年来，人们对机器学习技术及其应用越来越感兴趣。尽管框架和库已经为基于ML的系统的实现提供了密集的支持，但对工程学科和方法的研究仍处于早期阶段。这一领域最紧迫的问题是确定软件工程研究界的基本挑战，因为基于ML的系统的工程需要新的方法，因为基于ML的系统本质上是不同的。在本文中，我们分析了278名在实践中从事基于ML的系统的工作人员的问卷调查结果，阐明了实践者所感知的本质困难及其原因，并提出了潜在的研究方向。
There is increasing interest in machine learning (ML) techniques and their applications in recent years. Although there has been intensive support by frameworks and libraries for the implementation of ML-based systems, investigation into engineering disciplines and methods is still at the early phase. The most pressing issue in this field is identifying the essential challenges for the software engineering research community as engineering of ML-based systems requires novel approaches due to the essentially different nature of ML-based systems. In this paper, we analyze the results of a questionnaire administered to 278 people who have worked on ML-based systems in practice, clarify the essential difficulties and their causes as perceived by practitioners, and suggest potential research directions.