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dc.contributor.authorBarriga Rodriguez, Angela
dc.contributor.authorRutle, Adrian
dc.contributor.authorHeldal, Rogardt
dc.date.accessioned2023-03-24T13:47:28Z
dc.date.available2023-03-24T13:47:28Z
dc.date.created2022-05-24T13:05:17Z
dc.date.issued2022
dc.identifier.citationSoftware and Systems Modeling (SoSyM). 2022, 21 (3), 1135-1157.en_US
dc.identifier.issn1619-1366
dc.identifier.urihttps://hdl.handle.net/11250/3060396
dc.description.abstractArtificial intelligence has already proven to be a powerful tool to automate and improve how we deal with software development processes. The application of artificial intelligence to model-driven engineering projects is becoming more and more popular; however, within the model repair field, the use of this technique remains mostly an open challenge. In this paper, we explore some existing approaches in the field of AI-powered model repair. From the existing approaches in this field, we identify a series of challenges which the community needs to overcome. In addition, we present a number of research opportunities by taking inspiration from other fields which have successfully used artificial intelligence, such as code repair. Moreover, we discuss the connection between the existing approaches and the opportunities with the identified challenges. Finally, we present the outcomes of our experience of applying artificial intelligence to model repair.en_US
dc.language.isoengen_US
dc.publisherSpringeren_US
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.titleAI-powered model repair: an experience report—lessons learned, challenges, and opportunitiesen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionpublishedVersionen_US
dc.rights.holder© The Author(s) 2022en_US
dc.source.pagenumber1135-1157en_US
dc.source.volume21en_US
dc.source.journalSoftware and Systems Modeling (SoSyM)en_US
dc.source.issue3en_US
dc.identifier.doi10.1007/s10270-022-00983-5
dc.identifier.cristin2026963
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode2


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