Data-dependent grammars extend context-free grammars with arbitrary computation, variable binding, and constraints. These features provide the user with the freedom and power to express syntactic constructs outside the realm of context-free grammars, e.g., indentation rules in Haskell and type definitions in C. Data-dependent grammars have been recently presented by Jim et al. as a grammar formalism that enables construction of parsers from a rich format specification. Although some features of data-dependent grammars are available in current parsing tools, e.g., semantic predicates in ANTLR, data-dependent grammars have not yet fully found their way into practice. In this paper we present Iguana, a data-dependent parsing framework, implemented on top of the GLL parsing algorithm. In addition to basic features of data-dependent grammars, Iguana also provides high-level syntactic constructs, e.g., for operator precedence and indentation rules, which are implemented as desugaring to data-dependent grammars. These high-level constructs enable a concise and declarative way to define the syntax of programming languages. Moreover, Iguana's extensible data-dependent grammar API allows the user to easily add new high-level constructs or modify existing ones. We have used Iguana to parse various real programming languages, such as OCaml, Haskell, Java, and C#. In this paper we describe the architecture and features of Iguana, and report on its current implementation status.
International Conference on Compiler Construction
Software Analysis and Transformation

Afroozeh, A, & Izmaylova, A. (2016). Iguana: a practical data-dependent parsing framework. Presented at the International Conference on Compiler Construction. doi:10.1145/2892208.2892234