Boqi Chen, Aren A. Babikian, José Antonio Hernández López · 2026 · arXiv
DOI: 10.48550/arXiv.2610.29749 · open-access PDF
Model bahasa besar (LLM) semakin banyak digunakan untuk menghasilkan artefak rekayasa perangkat lunak yang ditulis dalam bahasa khusus domain (DSL). Instansi DSL yang benar biasanya harus mematuhi tidak hanya sintaks beton tetapi juga sintaks abstrak yang didefinisikan oleh metamodel yang diperluas dengan pembatasan semantik. pendekatan dekoding terbatas yang ada biasanya menjamin kepatuhan hanya dengan sintaks beton atau dengan set terbatas pembatasan semantik yang diungkapkan di atas teks yang dihasilkan, membuat konsistensi pembatasan tingkat metamodel sulit dipertahankan selama generasi.
Machine translation (Meta M2M100); the English original follows.
Large language models (LLMs) are increasingly used to generate software engineering artifacts written in domain-specific languages (DSLs). Correct DSL instances usually must comply with not only the concrete syntax but also the abstract syntax defined by a metamodel augmented with semantic well-formedness constraints. Existing constrained decoding approaches typically guarantee compliance only with concrete syntax or with a limited set of semantic constraints expressed over the generated text, making metamodel-level constraint consistency difficult to enforce during generation. We present MeMo
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