AI-Assisted Modeling: DSL-Driven AI Interactions
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arXiv
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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866915481526468608 |
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| author | Smyth, Steven Busch, Daniel Hmida, Moez Ben Haj Lee, Edward A. Steffen, Bernhard |
| author_facet | Smyth, Steven Busch, Daniel Hmida, Moez Ben Haj Lee, Edward A. Steffen, Bernhard |
| contents | AI-assisted programming greatly increases software development performance. We enhance this potential by integrating transparency through domain-specific modeling techniques and providing instantaneous, graphical visualizations that accurately represent the semantics of AI-generated code. This approach facilitates visual inspection and formal verification, such as model checking.
Formal models can be developed using programming, natural language prompts, voice commands, and stage-wise refinement, with immediate feedback after each transformation step. This support can be tailored to specific domains or intended purposes, improving both code generation and subsequent validation processes.
To demonstrate the effectiveness of this approach, we have developed a prototype as a Visual Studio Code extension for the Lingua Franca language. This prototype showcases the potential for novel domain-specific modeling practices, offering an advancement in how models are created, visualized, and verified. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_05160 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | AI-Assisted Modeling: DSL-Driven AI Interactions Smyth, Steven Busch, Daniel Hmida, Moez Ben Haj Lee, Edward A. Steffen, Bernhard Programming Languages Software Engineering AI-assisted programming greatly increases software development performance. We enhance this potential by integrating transparency through domain-specific modeling techniques and providing instantaneous, graphical visualizations that accurately represent the semantics of AI-generated code. This approach facilitates visual inspection and formal verification, such as model checking. Formal models can be developed using programming, natural language prompts, voice commands, and stage-wise refinement, with immediate feedback after each transformation step. This support can be tailored to specific domains or intended purposes, improving both code generation and subsequent validation processes. To demonstrate the effectiveness of this approach, we have developed a prototype as a Visual Studio Code extension for the Lingua Franca language. This prototype showcases the potential for novel domain-specific modeling practices, offering an advancement in how models are created, visualized, and verified. |
| title | AI-Assisted Modeling: DSL-Driven AI Interactions |
| topic | Programming Languages Software Engineering |
| url | https://arxiv.org/abs/2509.05160 |