An efficient context-free parsing algorithm
Communications of the ACM
Efficient Parsing for Natural Language: A Fast Algorithm for Practical Systems
Efficient Parsing for Natural Language: A Fast Algorithm for Practical Systems
Compiling language definitions: the ASF+SDF compiler
ACM Transactions on Programming Languages and Systems (TOPLAS)
Generalized Bottom Up Parsers With Reduced Stack Activity
The Computer Journal
BRNGLR: a cubic Tomita-style GLR parsing algorithm
Acta Informatica
Electronic Notes in Theoretical Computer Science (ENTCS)
Parse forest diagnostics with dr. ambiguity
SLE'11 Proceedings of the 4th international conference on Software Language Engineering
Science of Computer Programming
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We describe the development of space-efficient implementations of GLL parsers, and the process by which we refine a set-theoretic model of the algorithm into a practical parser generator that creates practical parsers. GLL parsers are recursive descent-like, in that the structure of the parser's code closely mirrors the grammar rules, and so grammars (and their parsers) may be debugged by tracing the running parser in a debugger. While GLL recognisers are straightforward to describe, full GLL parsers present technical traps and challenges for the unwary. In particular, naïve implementations based closely on the theoretical description of GLL can result in data structures that are not practical for grammars for real programming language grammars such as ANSI-C. We develop an equivalent formulation of the algorithm as a high-level set-theoretic model supported by table-based indices, in order to then explore a set of alternative implementations which trade space for time in ways which preserve the cubic bound.