Optimizing SGLR Parser Performance
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Abstract
The Scannerless Generalized-LR (SGLR) parsing algorithm allows parsing of declarative and modular syntax definitions. However, SGLR is notorious for having low performance, negatively impacting its adoption in practice. This paper presents several performance optimizations for JSGLR2, which is an implementation of SGLR. All optimizations are implemented and evaluated in parallel, which is possible due to JSGLR2's modular architecture. The evaluation is performed using existing sources from three different languages. A combined speed-up of 9% up to 44% is achieved, improving the practicality of JSGLR2.
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Research_Paper_1_.pdf
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