This research evaluates how well Large Language Models perform in understanding and generating complex software architecture designs for iOS applications.

• LLMs were assessed using Bloom's taxonomy to evaluate comprehension of the VIPER architecture pattern
• Study provides a structured evaluation framework for testing AI capabilities in software design tasks
• Results reveal important insights on AI's strengths and limitations in software architecture understanding

This research matters for Engineering teams considering AI-assisted software design, highlighting where LLMs can support architectural decisions and where human expertise remains essential.

Read the full paper: Assessing LLMs for Front-end Software Architecture Knowledge