A Case Study on Test Case Construction with Large Language Models: Unveiling Practical Insights and Challenges

• Roberto F. Lima Jr CESAR
• Luiz Fernando P. B. Presta CESAR School
• Lucca S. Borborema CESAR School
• Vanderson N. Silva CESAR
• Marcio L. M. Dahia CESAR
• Anderson Santos CESAR

DOI: https://doi.org/10.5753/cibse.2024.28465

Resumo

This study delves into the integration of Large Language Models (LLMs) in test case construction within software engineering, exploring their potential to enhance efficiency and effectiveness in test generation. Leveraging LLMs, known for their sophisticated natural language processing abilities, this research conducts a detailed case study on a representative software application to evaluate the practicality of LLMs in creating detailed and accurate test scenarios. The investigation focuses on the challenges and advantages of LLMs in test case development, assessing their impact on test comprehensiveness, accuracy, and the formulation process. By providing a nuanced understanding of LLMs’ role in software testing, this paper aims to inform practitioners and researchers about their potential and limitations, offering insights into their application in real-world testing environments and their contribution to advancing software testing methodologies.

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