Studying Software Engineering Patterns for Designing Machine Learning Systems

Hironori Washizaki, Hiromu Uchida, Foutse Khomh, Yann Gaël Guéhéneuc

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

Abstract

Machine-learning (ML) techniques are becoming more prevalent. ML techniques rely on mathematics and software engineering. Researchers and practitioners studying best practices strive to design ML systems and software that address software complexity and quality issues. Such design practices are often formalized as architecture and design patterns by encapsulating reusable solutions to common problems within given contexts. However, a systematic study to collect, classify, and discuss these software-engineering (SE) design patterns for ML techniques have yet to be reported. Our research collects good/bad SE design patterns for ML techniques to provide developers with a comprehensive classification of such patterns. Herein we report the preliminary results of a systematic-literature review (SLR) of good/bad design patterns for ML.

Original languageEnglish
Title of host publicationProceedings - 2019 10th International Workshop on Empirical Software Engineering in Practice, IWESEP 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages49-54
Number of pages6
ISBN (Electronic)9781728155906
DOIs
Publication statusPublished - 2019 Dec
Event10th International Workshop on Empirical Software Engineering in Practice, IWESEP 2019 - Tokyo, Japan
Duration: 2019 Dec 132019 Dec 14

Publication series

NameProceedings - 2019 10th International Workshop on Empirical Software Engineering in Practice, IWESEP 2019

Conference

Conference10th International Workshop on Empirical Software Engineering in Practice, IWESEP 2019
CountryJapan
CityTokyo
Period19/12/1319/12/14

Keywords

  • Anti-patterns
  • Architecture Patterns
  • Design Patterns
  • ML Patterns
  • Machine Learning

ASJC Scopus subject areas

  • Software
  • Safety, Risk, Reliability and Quality

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