Exploring the Use of Natural Language Processing Techniques for Enhancing Genetic Improvement

Oliver Krauss

Publikation: Beitrag in Buch/Bericht/TagungsbandKonferenzbeitragBegutachtung

1 Zitat (Scopus)

Abstract

We explore the potential of using large-scale Natural Language Processing (NLP) models, such as GPT-3, for enhancing genetic improvement in software development. These models have previously been used to automatically find bugs, or improve software. We propose utilizing these models as a novel mutator, as well as for explaining the patches generated by genetic improvement algorithms. Our initial findings indicate promising results, but further research is needed to determine the scalability and applicability of this approach across different programming languages.

OriginalspracheEnglisch
TitelProceedings - 2023 IEEE/ACM International Workshop on Genetic Improvement, GI 2023
Herausgeber (Verlag)Institute of Electrical and Electronics Engineers Inc.
Seiten21-22
Seitenumfang2
ISBN (elektronisch)9798350312324
DOIs
PublikationsstatusVeröffentlicht - 2023
Veranstaltung12th IEEE/ACM International Workshop on Genetic Improvement, GI 2023 - Hybrid, Melbourne, Australien
Dauer: 20 Mai 2023 → …

Publikationsreihe

NameProceedings - 2023 IEEE/ACM International Workshop on Genetic Improvement, GI 2023

Konferenz

Konferenz12th IEEE/ACM International Workshop on Genetic Improvement, GI 2023
Land/GebietAustralien
OrtHybrid, Melbourne
Zeitraum20.05.2023 → …

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