Non-human Modelers: Challenges and Roadmap for Reusable Self-explanation

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Abstract

Increasingly, software acts as a “non-human modeler” (NHM), managing a model according to high-level goals rather than a predefined script. To foster adoption, we argue that we should treat these NHMs as members of the development team. In our GrandMDE talk, we discussed the importance of three areas: effective communication (self-explanation and problem-oriented configuration), selection, and process integration. In this extended version of the talk, we will expand on the self-explanation area, describing its background in more depth and outlining a research roadmap based on a basic case study.

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  • grand2017-agd-extended

    Rights statement: © 2018 Springer Publishing. This is a post-peer-review, pre-copyedit version of an article published in Lecture Notes in Artificial Intelligence. The final authenticated version is available online at: http://dx.doi.org/10.1007/978-3-319-74730-9_14

    Accepted author manuscript, 430 KB, PDF-document

    Embargo ends: 23/01/19

Details

Publication date23 Jan 2018
Publication titleSoftware Technologies : Applications and Foundations - STAF 2017 Collocated Workshops, Revised Selected Papers
PublisherSpringer
Pages161-171
Number of pages11
Volume10748 LNCS
ISBN (Print)9783319747293
Original languageEnglish
EventInternational conference on Software Technologies: Applications and Foundations, STAF 2017 - Marburg, Germany

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10748 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceInternational conference on Software Technologies: Applications and Foundations, STAF 2017
CountryGermany
CityMarburg
Period17/07/1721/07/17

Bibliographic note

© 2018 Springer Publishing. This is a post-peer-review, pre-copyedit version of an article published in Lecture Notes in Artificial Intelligence. The final authenticated version is available online at: http://dx.doi.org/10.1007/978-3-319-74730-9_14

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Employable Graduates; Exploitable Research

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