On the Relation between Context-Free Grammars and Parsing Expression Grammars

Context-Free Grammars (CFGs) and Parsing Expression Grammars (PEGs) have several similarities and a few differences in both their syntax and semantics, but they are usually presented through formalisms that hinder a proper comparison. In this paper we present a new formalism for CFGs that highlights the similarities and differences between them. The new formalism borrows from PEGs the use of parsing expressions and the recognition-based semantics. We show how one way of removing non-determinism from this formalism yields a formalism with the semantics of PEGs. We also prove, based on these new formalisms, how LL(1) grammars define the same language whether interpreted as CFGs or as PEGs, and also show how strong-LL(k), right-linear, and LL-regular grammars have simple language-preserving translations from CFGs to PEGs

A Parser Generator Based on Earley\u27s Algorithm

Most parser generators are programs that take a context-free grammar specification for a language and generate a parser for that language. Usually, the parsers generated by these parser generators are based on some variations of LL(k) or LR(k) parsing algorithms. The parser generators discussed in this paper creates parsers based on Earlcy\u27s Algorithm. This parser generator creates parsers from any arbitrary context-free grammar specifications; even from ambiguous, cyclic, and unbounded look ahead grammar. These parsers are more powerful than LL(k) and LR(k) parsers and enable the user to create many new applications

Simple chain grammars

A subclass of the LR(0)-grammars, the class of simple chain grammars is introduced. Although there exist simple chain grammars which are not LL(k) for any k, this new class of grammars is very close related to the class of LL(1) and simple LL(1) grammars. In fact it can be proved (not in this paper) that each simple chain grammar has an equivalent simple LL(1) grammar. A very simple (bottom-up) parsing method is provided. This method follows directly from the definition of a simple chain grammar and can easily be given in terms of the well-known LR(0) parsing method

Context-Free Path Querying with Structural Representation of Result

Graph data model and graph databases are very popular in various areas such as bioinformatics, semantic web, and social networks. One specific problem in the area is a path querying with constraints formulated in terms of formal grammars. The query in this approach is written as grammar, and paths querying is graph parsing with respect to given grammar. There are several solutions to it, but how to provide structural representation of query result which is practical for answer processing and debugging is still an open problem. In this paper we propose a graph parsing technique which allows one to build such representation with respect to given grammar in polynomial time and space for arbitrary context-free grammar and graph. Proposed algorithm is based on generalized LL parsing algorithm, while previous solutions are based mostly on CYK or Earley algorithms, which reduces time complexity in some cases.Comment: Evaluation extende