Print Email Facebook Twitter 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 sglrparsingmodular architectureperformance 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 PDF modular_sglr.pdf 3.04 MB Close viewer /islandora/object/uuid%3A7d9f9bcc-117c-4617-860a-4e3e0bbc8988/datastream/OBJ/view