A Survey of Testing Techniques Based on Large Language Models

被引：0

作者：

Qi, Fei ^{[1
]}

Hou, Yingnan ^{[1
]}

Lin, Ning ^{[1
]}

Bao, Shanshan ^{[1
]}

Xu, Nuo ^{[1
]}

机构：

[1] Harbin Space Star Data Syst Technol Co Ltd, Harbin 150028, Peoples R China

来源：

PROCEEDINGS OF 2024 INTERNATIONAL CONFERENCE ON COMPUTER AND MULTIMEDIA TECHNOLOGY, ICCMT 2024 | 2024年

关键词：

LLM; Software Testing Techniques; Pre-trained Large Language Model;

D O I：

10.1145/3675249.3675298

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

With the development of software testing technology, Large Language Model (LLM) driven testing method have gradually become an emerging trend in the field of software testing. This paper presents a comprehensive review of LLM-based testing techniques. The results of 19 studies using LLM to optimize testing techniques are analyzed from the perspective of software testing. This paper discusses in detail how to use LLM to optimize test techniques for generating automated test code and generating diverse input in software test tasks. It also summarizes the challenges and opportunities faced by this field. The above conclusions can identify the shortcomings of LLM-based software testing technology and the direction of future research.

引用

页码：280 / 284

页数：5

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