DynEx: Dynamic Code Synthesis with Structured Design Exploration for Accelerated Exploratory Programming
<|reference_start|>DynEx: Dynamic Code Synthesis with Structured Design Exploration for Accelerated Exploratory Programming: Recent advancements in large language models have significantly expedited the process of generating front-end code. This allows users to rapidly prototype user interfaces and ideate through code, a process known as exploratory programming. However, existing LLM code-generation tools focus more on technical implementation details rather than finding the right design given a particular problem. We present DynEx, an LLM-based method for design exploration in accelerated exploratory programming. DynEx uses LLMs to guide users through a structured Design Matrix to explore the design space before dynamic iterative implementation. It also introduces a technique to self-invoke generative AI, enabling the creation of a diverse suite of applications. A user study of 10 experts found that DynEx increased design exploration and enabled the creation of more complex and varied prototypes compared to a Claude Artifact baseline. We conclude with a discussion of the implications of design exploration for exploratory programming.<|reference_end|>
@article{ma2024dynex:,
    title={DynEx: Dynamic Code Synthesis with Structured Design Exploration for
  Accelerated Exploratory Programming},
    author={Jenny Ma, Karthik Sreedhar, Vivian Liu, Sitong Wang, Pedro Alejandro
  Perez, Riya Sahni, Lydia B. Chilton},
    journal={arXiv preprint arXiv:2410.00400},
    year={2024},
    archivePrefix={arXiv},
    eprint={2410.00400},
    primaryClass={cs.HC}
}