2015/01/11 by Luis Quesada, Quesada, Luis, Fernando Berzal +3
Biochemistry, Genetics and Molecular Biology · Computer Science · #Algorithms and Data Compression #DNA and Biological Computing #FOS: Computer and information sciences #Formal Languages and Automata Theory (cs.FL) #semigroups and automata theory
paper · pdf · doi:10.48550/arxiv.1501.02795
openalex publication_date 2015/01/11 · openalex created_date 2016/06/24 · openalex updated_date 2026/07/28
Traditional language processing tools constrain language designers to specific kinds of grammars. In contrast, model-based language processing tools decouple language design from language processing. These tools allow the occurrence of lexical and syntactic ambiguities in language specifications and the declarative specification of constraints for resolving them. As a result, these techniques require scanners and parsers able to parse context-free grammars, handle ambiguities, and enforce constraints for disambiguation. In this paper, we present Lamb and Fence. Lamb is a scanning algorithm that supports ambiguous token definitions and the specification of custom pattern matchers and constraints. Fence is a chart parsing algorithm that supports ambiguous context-free grammars and the definition of constraints on associativity, composition, and precedence, as well as custom constraints. Lamb and Fence, in conjunction, enable the implementation of the ModelCC model-based language processing tool.