Generalised Parsing: Some Costs

Abstract

We discuss generalisations of bottom up parsing, emphasising the relative costs for real programming languages. Our goal is to provide a roadmap of the available approaches in terms of their space and time performance for programming language applications, focusing mainly on GLR style algorithms. It is well known that the original Tomita GLR algorithm fails to terminate on hidden left recursion: here we analyse two approaches to correct GLR parsing (i) the modification due to Farshi that is incorporated into Visser’s work and (ii) our own right-nullable GLR (RNGLR) algorithm, showing that Farshi’s approach can be expensive. We also present results from our new Binary RNGLR algorithm which is asymptotically the fastest parser in this family and show that the recently reported reduction incorporated parsers can require automata that are too large to be practical on current machines. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.