2015/03/29 by Vadim Zaytsev, Zaytsev, Vadim
Biochemistry, Genetics and Molecular Biology · Computer Science · #DNA and Biological Computing #F.4.2 #F.4.3 #FOS: Computer and information sciences #Formal Languages and Automata Theory (cs.FL) #I.2.3 #Natural Language Processing Techniques #Programming Languages (cs.PL) #Semantic Web and Ontologies #Software Engineering (cs.SE) #cs.FL #cs.PL #cs.SE
paper · pdf · doi:10.48550/arxiv.1503.08476
In Poster Proceedings of 6th Conference on Software Language Engineering (SLE) 2013, http://www.sleconf.org/2013/
arxiv created 2015/03/29 · openalex publication_date 2015/03/29 · arxiv updated 2015/03/31 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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.