LLMs and Prompting for Unit Test Generation: A Large-Scale Evaluation
Abstract
Unit testing, essential for identifying bugs, is often neglected due to time constraints. Automated test generation tools exist but typically lack readability and require developer intervention. Large Language Models (LLMs) like GPT and Mistral show potential in test generation, but their effectiveness remains unclear.
BibTeX
@inproceedings{Ouedraogo-al:ASE24,
author = {Wendk{\^{u}}uni C. Ou{\'{e}}draogo and
Abdoul Kader Kabor{\'{e}} and
Haoye Tian and
Yewei Song and
Anil Koyuncu and
Jacques Klein and
David Lo and
Tegawend{\'{e}} F. Bissyand{\'{e}}},
title = {{LLMs} and Prompting for Unit Test Generation: A {Large-Scale} Evaluation},
booktitle = {ASE},
pages = {2464--2465},
publisher = {{ACM}},
year = {2024},
}