A taxonomy of software engineering challenges for machine learning systems : An empirical investigation

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A taxonomy of software engineering challenges for machine learning systems : An empirical investigation

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Publication Paper in proceeding
Title A taxonomy of software engineering challenges for machine learning systems : An empirical investigation
Author Lwakatare, Lucy ; Raj, Aiswarya ; Bosch, Jan ; Olsson Holmström, Helena ; Crnkovic, Ivica
Editor Kruchten, Philippe ; Fraser, Steven ; Coallier, François
Date 2019
English abstract
Artificial intelligence enabled systems have been an inevitable part of everyday life. However, efficient software engineering principles and processes need to be considered and extended when developing AI- enabled systems. The objective of this study is to identify and classify software engineering challenges that are faced by different companies when developing software-intensive systems that incorporate machine learning components. Using case study approach, we explored the development of machine learning systems from six different companies across various domains and identified main software engineering challenges. The challenges are mapped into a proposed taxonomy that depicts the evolution of use of ML components in software-intensive system in industrial settings. Our study provides insights to software engineering community and research to guide discussions and future research into applied machine learning.
Conference
XP 2019: Agile Processes in Software Engineering and Extreme Programming (May 21 - 25 : Montreal, Canada)
DOI https://doi.org/10.1007/978-3-030-19034-7_14 (link to publisher's fulltext.)
Link https://link.springer.com/chapter/10.1007/978-3-030-19034-7_14 .Icon
Publisher Springer
Host/Issue Agile Processes in Software Engineering and Extreme Programming : 20th International Conference, XP 2019, Montréal, QC, Canada, May 21–25, 2019, Proceedings;
Series/Issue Lecture Notes in Business Information Processing;355
ISBN 978-3-030-19033-0
978-3-030-19033-0
Language eng (iso)
Subject Artificial intelligence
Machine learning
Software engineering
Challenges
Technology
Research Subject Categories::TECHNOLOGY
Handle http://hdl.handle.net/2043/28600 Permalink to this page
Link https://www.agilealliance.org/xp2019/... (external link to related web page)
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