引导语法收敛
Guided Grammar Convergence
摘要：
形式语法的关联是一个很难的问题，它需要在语言等价（已知是不可判定的）和语法同一（微不足道的）之间取得平衡。在本文中，我们调查这两个极端之间的几个里程碑，并提出了一种方法，在语法工程的不一致性管理。虽然传统的语法收敛是一种依赖于人类专家将差异编码为转换步骤的实用方法，但引导语法收敛是一种适用范围更窄的技术，其通过规范化语法并在它们之间建立结构等价关系来自动推断这种转换步骤。这使我们能够执行一个案例研究，自动推断11个语法（广义上）之间的双向转换相同的人工功能语言：解析器规范与不同的组合子库，定子句语法，具体的语法定义，代数数据类型，元模型，XML模式，对象模型。
英文摘要：
Relating formal grammars is a hard problem that balances between language equivalence (which is known to be undecidable) and grammar identity (which is trivial). In this paper, we investigate several milestones between those two extremes and propose a methodology for inconsistency management in grammar engineering. While conventional grammar convergence is a practical approach relying on human experts to encode differences as transformation steps, guided grammar convergence is a more narrowly applicable technique that infers such transformation steps automatically by normalising the grammars and establishing a structural equivalence relation between them. This allows us to perform a case study with automatically inferring bidirectional transformations between 11 grammars (in a broad sense) of the same artificial functional language: parser specifications with different combinator libraries, definite clause grammars, concrete syntax definitions, algebraic data types, metamodels, XML schemata, object models.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
