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Chances and Challenges of LLM-based Software Reengineering

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dc.contributor.authorQuante, Jochen
dc.contributor.authorWoehrle, Matthias
dc.contributor.editorHerrmann, Andrea
dc.date.accessioned2024-07-26T10:37:41Z
dc.date.available2024-07-26T10:37:41Z
dc.date.issued2024
dc.description.abstractLarge Language Models (LLMs) have opened up unforeseen new possibilities. They deliver amazing results for complex text-based tasks for which no satisfactory automated solution was available before. This is even more astonishing as they just calculate the most probable subsequent token, given a sequence of tokens. This is also true for software development support: There are various software engineering task for which LLMs show potential. In this paper, we discuss the potential and current shortcomings of LLM-based approaches for selected Software Reengineering tasks with a focus on language translation. All experiments reported in the following were performed with GPT-4.en
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/44182
dc.language.isoen
dc.pubPlaceBonn
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofSoftwaretechnik-Trends Band 44, Heft 2
dc.relation.ispartofseriesSoftwaretechnik-Trends
dc.subjectLarge Language Model
dc.subjectGPT
dc.subjectSoftware Reengineering
dc.titleChances and Challenges of LLM-based Software Reengineeringen
dc.typeText/Conference Paper
mci.conference.date29.-30. April 2024
mci.conference.locationBad Honnef
mci.conference.sessiontitle26. Workshop Software-Reengineering und -Evolution (WSRE)
mci.reference.pages46-47

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Softwaretechnik-Trends 44(2) - 2024