gogll

Copyright 2019 Marius Ackerman. See Apache license.

News

2019-09-09

The performance of the BSR has been improved. The time for gogll to compile gogll.md is reduced from 1.3s to 0.2s

Gogll

Gogll generates scannerless, clustered nonterminal parsers (CNP) following Scott et al 2019. CNP is a version of generalised LL parsing (GLL)Scott & Johnstone 2016. GLL parsers can parse all context free (CF) languages.

Benefits and disadvantages

The following table compares GLL parsers with LL-k/LR-k parsers and PEGs

• General CF grammars allow the parser developer to write grammars that match the language most naturally.
• Composability allows pre-existing grammar modules to be imported.
• GLL produces a forest of all valid parses of a string. This provides a more systematic basis for disambiguation than k>1 lookahead and solves the problem of PEGs that hide ambiguity by selecting the first valid parse.
• Operator precedence can be implemented very easily by disambiguating the parse forest [Afroozeh et al 2013, Basten & Vinju 2012].

But

• Most non-trivial context free grammars will generate ambiguous parsers, requiring explicit disambiguation.
• A scannerless GLL parser is slower than the equivalent LR1 parser. See the performance figures for compiling gogll.md in the table above. I expect to improve the performance of gogll but GLL parsers are likely to remain significantly slower than equivalent LL-1/LR-1 parsers.
• GLL parsers are worst-case cubic in time and space complexity. The LL-1 parts of the grammar have linear complexity.

Input Symbols, Markdown Files

Gogll accepts UTF-8 input strings. A gogll parser has two parse functions:

• Parse(I []byte) []*ParseError
• func ParseFile(fname string) []*ParseError
  If fname ends with .md the parser ignores all text outside the markdown code blocks delimited by triple backticks. See gogll.md for an example.

Gogll Grammar

Gogll v1 has a BNF grammar. See gogll.md

Status

• gogll v0 was a bootstrap compiler implemented by a gocc lexer and parser.
• gogll v0 was used to compile gogll v1.
• gogll v0 is currently used to compile a proprietary a query language.
• gogll v1 compiles itself
• The query language mentioned above is being migrated to gogll v1.
• gogll v1 is currently being used to implement a proprietary GUI definition language.

gogll v1 is actively being developed.

Features considered for future implementation

1. EBNF grammar support Scott&Johnstone 2018.
2. Error reporting for normal people.
3. Better documentation, including how to traverse the binary subtree reprentation (BSR) of the parse forest.

Documentation

At the moment this document and the gogll grammar are the only documentation. Have a look at gogll/examples/ambiguous for a simple example and also for simple disambiguation.

Alternatively look at gogll.md which is the input grammar and also the grammar from which the parser for this version of gogll was generated. gogll/da disambiguates the parse forest for an input string.

Changelog

see

Bibliography

• Elizabeth Scott, Adrian Johnstone and L. Thomas van Binsbergen.
  Derivation representation using binary subtree sets.
  In: Science of Computer Programming (175) 2019

• Elizabeth Scott and Adrian Johnstone.
  GLL Syntax Analysers For EBNF Grammars.
  In: Science of Computer Programming Volume 166, 15 November 2018

• Elizabeth Scott and Adrian Johnstone.
  Structuring the GLL parsing algorithm for performance.
  In: Science of Computer Programming Volume 125, 1 September 2016

• Ali Afroozeh, Mark van den Brand, Adrian Johnstone, Elizabeth Scott, Jurgen Vinju.
  Safe Specification of Operator Precedence Rules.
  In: Erwig M., Paige R.F., Van Wyk E. (eds) Software Language Engineering. SLE 2013. Lecture Notes in Computer Science, vol 8225. Springer, Cham

• Basten H.J.S., Vinju J.J. (2012) Parse Forest Diagnostics with Dr. Ambiguity. In: Sloane A., Aßmann U. (eds) Software Language Engineering. SLE 2011. Lecture Notes in Computer Science, vol 6940. Springer, Berlin, Heidelberg

• Bryan Ford. Parsing Expression Grammars: A Recognition-Based Syntactic Foundation.