Undoing Software Engineering

Demodularization of a SGLR Parser for Performance Gains

Bachelor thesis (2021)

Authors

M. Kapitonenko Electrical Engineering, Mathematics and Computer Science

Contributors

J. Denkers Programming Languages - EEMCS (supervisor 1)
D.A.A. Pelsmaeker Programming Languages - EEMCS (supervisor 2)
Eelco Visser Programming Languages - EEMCS (supervisor 2)
Ranga Rao Venkatesha Prasad Embedded Systems - EEMCS (coach)
Faculty
Electrical Engineering, Mathematics and Computer Science
Copyright: © 2021 Nik Kapitonenko
Refactoring SGLR Parsing
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Published Date

02-07-2021

Language

English

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Faculty

Electrical Engineering, Mathematics and Computer Science

Abstract

JSGLR2 is a java implementation of the Scannerless Generalized LR-parsing (SGLR) algorithm. It employs a modular architecture. This architecture comes with a performance overhead for letting multiple components interact with each other. This paper looks into the size of the performance overhead penalty for the recovery parser variant. It does so by creating an 'inlined' version of the recovery parser variant. The inlined recovery variant is a JSGLR2 implementation that ignores the modular architecture, and hard-codes the components. The performance of the inlined variant is measured with a pre-existing evaluation suite. The results show that there is a performance increase between the original, and the inlined variant.