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Preliminary Systematic Literature Review of Machine Learning System Development Process

10/12/2019

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by Yasuhiro Watanabe, et al.

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Previous machine learning (ML) system development research suggests that emerging software quality attributes are a concern due to the probabilistic behavior of ML systems. Assuming that detailed development processes depend on individual developers and are not discussed in detail. To help developers to standardize their ML system development processes, we conduct a preliminary systematic literature review on ML system development processes. A search query of 2358 papers identified 7 papers as well as two other papers determined in an ad-hoc review. Our findings include emphasized phases in ML system developments, frequently described practices and tailored traditional software development practices.

Yasuhiro Watanabe
1 publication
Hironori Washizaki
7 publications
Kazunori Sakamoto
1 publication
Daisuke Saito
5 publications
Kiyoshi Honda
1 publication
Naohiko Tsuda
1 publication
Yoshiaki Fukazawa
2 publications
Nobukazu Yoshioka
4 publications

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