A carregar...
Publicação
Applying large language models to software develop-ment: enhancing requirements, design and code
| Nome: | Descrição: | Tamanho: | Formato: | |
|---|---|---|---|---|
| 365.92 KB | Adobe PDF |
Orientador(es)
Resumo(s)
This paper explores the potential of Large Language Models (LLM) to optimize various stages of the software development lifecycle, including require-ments elicitation, architecture design, diagram creation, and implementation. The study is grounded in a real-world case, where development time and result quality are compared with and without LLM assistance. This research underscores the possibility of applying prompt patterns in LLM to support and enhance software development activities, focusing on a B2C digital commerce platform centered on fashion retail, designated LUNA. The methodology adopted is Design Sci-ence, which follows a practical and iterative approach. Requirements, design sug-gestions, and code samples are analyzed before and after the application of lan-guage models. The results indicate substantial advantages in the development process, such as improved task efficiency, faster identification of requirement gaps, and enhanced code readability. Nevertheless, challenges were observed in interpreting complex business logic. Future work should explore the integration of LLM with domain-specific ontologies and business rule engines to improve contextual accuracy in code and model generation. Additionally, refining prompt engineering strategies and combining LLM with interactive development envi-ronments could further enhance code quality, traceability, and explainability.
Descrição
Palavras-chave
Large Language Models Prompt Engineering Software Develop-ment Lifecycle
Contexto Educativo
Citação
Santos, G., Silveira, C., Santos, V., Santos, A., & Mamede, H. (2025, July). Applying Large Language Models to Software Development: Enhancing Requirements, Design and Code. In International Conference on Disruptive Technologies, Tech Ethics and Artificial Intelligence (pp. 226-239). Cham: Springer Nature Switzerland.
Editora
Springer Nature
Licença CC
Sem licença CC