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Tooling for Developing Data-Driven Applications: Overview and Outlook

dc.contributor.authorWeber, Thomas
dc.contributor.authorHußmann, Heinrich
dc.contributor.editorMühlhäuser, Max
dc.contributor.editorReuter, Christian
dc.contributor.editorPfleging, Bastian
dc.contributor.editorKosch, Thomas
dc.contributor.editorMatviienko, Andrii
dc.contributor.editorGerling, Kathrin|Mayer, Sven
dc.contributor.editorHeuten, Wilko
dc.contributor.editorDöring, Tanja
dc.contributor.editorMüller, Florian
dc.contributor.editorSchmitz, Martin
dc.date.accessioned2022-08-31T09:43:04Z
dc.date.available2022-08-31T09:43:04Z
dc.date.issued2022
dc.description.abstractMachine Learning systems are, by now, an essential part of the software landscape. From the development perspective this means a paradigmatic shift, which should be reflected in the way we write software. For now, the majority of developers relies on traditional tools for data-driven development, though. To determine how research into tools is catching up, we conducted a systematic literature review, searching for tools dedicated to data-driven development. Of the 1511 search results, we analyzed 76 relevant publications in detail. The diverse sample indicated a strong interest in this topic from different domains, with different approaches and methods. While there are a number of common trends, e.g. the use of visualization, in these tools, only a limited, although increasing, number of these tools has so far been evaluated comprehensively. We therefore summarize trends, strengths and weaknesses in the status quo for data-driven development tools and conclude with a number of potential future directions this field.en
dc.description.urihttps://dl.acm.org/doi/10.1145/3543758.3543779en
dc.identifier.doi10.1145/3543758.3543779
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/39260
dc.language.isoen
dc.publisherACM
dc.relation.ispartofMensch und Computer 2022 - Tagungsband
dc.relation.ispartofseriesMensch und Computer
dc.subjectLiterature Review
dc.subjectSoftware Development
dc.subjectTools
dc.subjectMachine Learning
dc.subjectData-Driven Development
dc.titleTooling for Developing Data-Driven Applications: Overview and Outlooken
dc.typeText/Conference Paper
gi.citation.endPage77
gi.citation.publisherPlaceNew York
gi.citation.startPage66
gi.conference.date4.-7. September 2022
gi.conference.locationDarmstadt
gi.conference.sessiontitleMCI-SE02: Tools and Technology
gi.document.qualitydigidoc

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