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Generative AI to Generate Test Data Generators

delete2024-11-01
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OA
AI
B
Benoît Baudry *
K
Khashayar Etemadi
S
Sen Fang
Y
Yogya Gamage
Y
Yi Liu
Y
Yuxin Liu
M
Martin Monperrus
J
Javier Ron
A
André Silva
D
Deepika Tiwari
DOI：10.1109/MS.2024.3418570delete
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Abstract

Abstract

En 中文
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.
Keywords:
Generators
Cultural differences
Testing
Libraries
Java
Codes
Vectors

Journal

IEEE Software cover
IEEE Software
IF:
3
Papers:
3.1K
Citations:
3.6K

Organization

U
universite de montreal
Scholars:
4.6W
Papers: 3.8W
Citations: 46
R
Royal Institute of Technology
Scholars:
1.8W
Papers: 1.8W
Citations: 25
N
North Carolina State University
Scholars:
2.6W
Papers: 2.3W
Citations: 3.7W
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