A Modular SGLR Parsing Architecture for Systematic Performance Optimization

Title

A Modular SGLR Parsing Architecture for Systematic Performance Optimization

 Author

Denkers, Jasper (TU Delft Electrical Engineering, Mathematics and Computer Science)

Contributor

De Souza Amorim, Eduardo (mentor)
Steindorfer, Michael (mentor)
Visser, Eelco (mentor)

Degree granting institution

Delft University of Technology

 Date

2018-01-24

 Abstract

SGLR parsing is an approach that enables parsing of context-free languages by means of declarative, concise and maintainable syntax definition. Existing implementations suffer from performance issues and their architectures are often highly coupled without clear separation between their components. This work introduces a modular SGLR architecture with several variants implemented for its components to systematically benchmark and improve performance. This work evaluates these variants both independently and combined using artificial and real world programming languages grammars. The architecture is implemented in Java as JSGLR2, the successor of the original parser in Spoofax, interpreting parse tables generated by SDF3. The improvements combined result into a parsing and imploding time speedup from 3x on Java to 10x on GreenMarl with respect to the previous JSGLR implementation.

 Subject

sglr
parsing
modular architecture
performance optimization

 To reference this document use:

http://resolver.tudelft.nl/uuid:7d9f9bcc-117c-4617-860a-4e3e0bbc8988

 Part of collection

Student theses

 Document type

master thesis

 Rights

© 2018 Jasper Denkers
Files
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