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Code generation through Large Language Models (LLMs) has made significant progress in recent years. However, when the code generation involves a lesser-known Domain-Specific Language (DSL), a standard tool in software development for cyber-physical systems, LLMs’ performance significantly decreases. We present an exploratory study assessing LLMs’ performance in generating LIrAs (Language for Interactive Agents) code, a DSL for robotic and multi-agent tasks specification. This work is a stepping stone towards improving LLM-generated DSL code through iterative specification repair techniques driven by formal verification results.

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Preliminary Study of DSL Code Generation for Robotics with LLMs

  • 会议论文

  • 发表日期：

    2026年

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  • Alberto Tagliaferro,
  • Livia Lestingi,
  • Matteo Rossi

摘要

Code generation through Large Language Models (LLMs) has made significant progress in recent years. However, when the code generation involves a lesser-known Domain-Specific Language (DSL), a standard tool in software development for cyber-physical systems, LLMs’ performance significantly decreases. We present an exploratory study assessing LLMs’ performance in generating LIrAs (Language for Interactive Agents) code, a DSL for robotic and multi-agent tasks specification. This work is a stepping stone towards improving LLM-generated DSL code through iterative specification repair techniques driven by formal verification results.