Leveraging LLMs for Multi-File DSL Code Generation: An Industrial Case Study
Large language models (LLMs) perform strongly on general-purpose code generation, yet their applicability to enterprise domain-specific languages (DSLs) remains underexplored, especially for repository-scale change generation spanning multiple files and folder structures from a single natural-language (NL) instruction. We report an industrial case study at BMW that adapts code-oriented LLMs to generate and modify project-root DSL artifacts for an Xtext-based DSL that drives downstream Java/TypeScript code generation. We develop an end-to-end pipeline for dataset construction, multi-file task representation, model adaptation, and evaluation. We encode DSL folder hierarchies as structured, ...
| Authors | Sivajeet Chand, Kevin Nguyen, Peter Kuntz et al. |
|---|---|
| Primary category | cs.SE |
| Published | 27 April 2026 |
| Last updated at source | 27 April 2026 |
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