Generative AI to Generate Test Data Generators 2024 (English)In: IEEE Software, ISSN 0740-7459, E-ISSN 1937-4194, Vol. 41, no 6, p. 55-64Article in journal (Refereed) Published

Abstract [en]

High quality data is essential for designing effective software test suites. We propose three original methods for using large language models to generate representative test data, which fit to the domain of the program under test and are culturally adequate.

Place, publisher, year, edition, pages

Institute of Electrical and Electronics Engineers (IEEE) , 2024. Vol. 41, no 6, p. 55-64

Keywords [en]

Generators, Cultural differences, Testing, Libraries, Java, Codes, Vectors

National Category

Software Engineering

Identifiers

URN: urn:nbn:se:kth:diva-355309DOI: 10.1109/MS.2024.3418570ISI: 001329864000010Scopus ID: 2-s2.0-85197039632OAI: oai:DiVA.org:kth-355309DiVA, id: diva2:1909148

Funder

Wallenberg AI, Autonomous Systems and Software Program (WASP)Swedish Foundation for Strategic Research, chains

Note

QC 20241030

Available from: 2024-10-30 Created: 2024-10-30 Last updated: 2024-12-10Bibliographically approved

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Etemadi, KhashayarGamage, YogyaLiu, YuxinMonperrus, MartinRon Arteaga, JavierSilva, AndreTiwari, Deepika

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Etemadi, KhashayarGamage, YogyaLiu, YiLiu, YuxinMonperrus, MartinRon Arteaga, JavierSilva, AndreTiwari, Deepika

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Theoretical Computer Science, TCSSoftware and Computer systems, SCS

In the same journal

IEEE Software

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Software Engineering

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