Software Architecture and Machine Learning (Dagstuhl Seminar 23302)

Authors Grace A. Lewis, Henry Muccini, Ipek Ozkaya, Karthik Vaidhyanathan, Roland Weiss, Liming Zhu and all authors of the abstracts in this report



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Author Details

Grace A. Lewis
  • Carnegie Mellon Software Engineering Institute - Pittsburgh, US
Henry Muccini
  • University of L'Aquila, IT
Ipek Ozkaya
  • Carnegie Mellon Software Engineering Institute - Pittsburgh, US
Karthik Vaidhyanathan
  • IIIT Hyderabad, IN
Roland Weiss
  • ABB - Mannheim, DE
Liming Zhu
  • Data61, CSIRO - Sydney, AU
and all authors of the abstracts in this report

Cite As Get BibTex

Grace A. Lewis, Henry Muccini, Ipek Ozkaya, Karthik Vaidhyanathan, Roland Weiss, and Liming Zhu. Software Architecture and Machine Learning (Dagstuhl Seminar 23302). In Dagstuhl Reports, Volume 13, Issue 7, pp. 166-188, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024) https://doi.org/10.4230/DagRep.13.7.166

Abstract

This report documents the program and outcomes of Dagstuhl Seminar 23302, "Software Architecture and Machine Learning". We summarize the goals and format of the seminar, results from the breakout groups, key definitions relevant to machine learning-enabled systems that were discussed, and the research roadmap that emerged from the discussions during the seminar. The report also includes the abstracts of the talks presented at the seminar and summaries of open discussions.

Subject Classification

ACM Subject Classification
  • Software and its engineering → Software architectures
  • Computing methodologies → Machine learning
  • Software and its engineering → Extra-functional properties
  • Computing methodologies → Artificial intelligence
  • Software and its engineering
Keywords
  • Architecting ML-enabled Systems
  • ML for Software Architecture
  • Software Architecture for ML
  • Machine Learning
  • Software Architecture
  • Software Engineering

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