This paper presents a detailed case study examining the application of Large Language Models (LLMs) in the construction of test cases within the context of software engineering. LLMs, characterized by their advanced natural language processing capabilities, are increasingly garnering attention as tools to automate and enhance various aspects of the software development lifecycle. Leveraging a case study methodology, we systematically explore the integration of LLMs in the test case construction process, aiming to shed light on their practical efficacy, challenges encountered, and implications for software quality assurance. The study encompasses the selection of a representative software application, the formulation of test case construction methodologies employing LLMs, and the subsequent evaluation of outcomes. Through a blend of qualitative and quantitative analyses, we assess the impact of LLMs on test case comprehensiveness, accuracy, and efficiency. Additionally, we delve into challenges such as model interpretability, ethical considerations, and adaptation to diverse software contexts. The findings from this case study contribute nuanced insights into the practical utility of LLMs in the domain of test case construction, elucidating their potential benefits and limitations. By addressing real-world scenarios and complexities, this research aims to inform software practitioners and researchers alike about the tangible implications of incorporating LLMs into the software testing landscape, fostering a more comprehensive understanding of their role in optimizing the software development process.

翻译：本文通过详细案例研究，系统考察了大型语言模型（LLMs）在软件工程测试用例构建中的应用。基于其在自然语言处理方面的先进能力，LLMs作为自动化与增强软件开发全生命周期各环节的工具正日益受到关注。我们采用案例研究方法，系统探索了LLMs与测试用例构建过程的整合，旨在揭示其实践效能、面临挑战以及对软件质量保证的启示。研究涵盖代表性软件应用的选择、基于LLMs的测试用例构建方法设计及后续效果评估。通过定性与定量相结合的分析，我们评估了LLMs对测试用例全面性、准确性和效率的影响。此外，还深入探讨了模型可解释性、伦理考量及对多样化软件场景的适配性等挑战。本案例研究为LLMs在测试用例构建领域的实际实用价值提供了精细化洞见，阐明了其潜在优势与局限性。通过聚焦现实场景与复杂问题，本研究旨在帮助软件从业者与研究人员深入了解将LLMs融入软件测试领域的切实影响，促进对其优化软件开发流程作用的全面认知。