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DSL-Xpert 2.0: Enhancing LLM-Driven code generation for domain-specific languages
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DOI：10.1016/j.infsof.2025.107954.png)
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Abstract
En 中文
Domain-specific languages (DSLs) are essential for modeling specialized concepts, offering greater fluency and efficiency than general-purpose languages. However, their adoption is often hindered by steep learning curves, limited tools, and complex implementations. While large language models (LLMs) can generate DSL code from natural language, their performance is limited in niche areas due to a lack of training on specific DSL definitions.
Keywords:
Domain-specific languages (DSLs)
Large language models (LLMs)
Semantic parsing
Grammar prompting
Few-shot learning
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