Designing domain models and software architectures represents a significant challenge in software development, as the resulting architectures play a vital role in fulfilling the system's quality of service. Due to time pressure, architects often model only one architecture based on their known limited domain understanding, patterns, and experience instead of thoroughly analyzing the domain and evaluating multiple candidates, selecting the best fitting. Existing approaches try to generate domain models based on requirements, but still require time-consuming manual effort to achieve good results. Therefore, in this vision paper, we propose a method to generate software architecture candidates semi-automatically based on requirements using artificial intelligence techniques. We further envision an automatic evaluation and trade-off analysis of the generated architecture candidates using, e.g., the architecture trade-off analysis method combined with large language models and quantitative analyses. To evaluate this approach, we aim to analyze the quality of the generated architecture models and the efficiency and effectiveness of our proposed process by conducting qualitative studies.

翻译：设计领域模型和软件架构是软件开发中的重大挑战，因为最终架构在满足系统服务质量方面起着关键作用。由于时间压力，架构师往往仅基于自身有限的领域理解、经验和模式进行单一架构建模，而非深入分析领域需求、评估多个候选方案并择优选取。现有方法试图根据需求生成领域模型，但要取得良好效果仍需耗费大量人工。因此，在这篇愿景论文中，我们提出一种基于人工智能技术、从需求半自动化生成软件架构候选方案的方法。我们进一步设想结合架构权衡分析方法与大型语言模型及量化分析，对生成的候选架构进行自动评估与权衡分析。为评估该方法，我们计划通过定性研究，分析所生成架构模型的质量，以及所提流程的效率与有效性。