2,138 research outputs found
Towards Zero-Overhead Disambiguation of Deep Priority Conflicts
**Context** Context-free grammars are widely used for language prototyping
and implementation. They allow formalizing the syntax of domain-specific or
general-purpose programming languages concisely and declaratively. However, the
natural and concise way of writing a context-free grammar is often ambiguous.
Therefore, grammar formalisms support extensions in the form of *declarative
disambiguation rules* to specify operator precedence and associativity, solving
ambiguities that are caused by the subset of the grammar that corresponds to
expressions.
**Inquiry** Implementing support for declarative disambiguation within a
parser typically comes with one or more of the following limitations in
practice: a lack of parsing performance, or a lack of modularity (i.e.,
disallowing the composition of grammar fragments of potentially different
languages). The latter subject is generally addressed by scannerless
generalized parsers. We aim to equip scannerless generalized parsers with novel
disambiguation methods that are inherently performant, without compromising the
concerns of modularity and language composition.
**Approach** In this paper, we present a novel low-overhead implementation
technique for disambiguating deep associativity and priority conflicts in
scannerless generalized parsers with lightweight data-dependency.
**Knowledge** Ambiguities with respect to operator precedence and
associativity arise from combining the various operators of a language. While
*shallow conflicts* can be resolved efficiently by one-level tree patterns,
*deep conflicts* require more elaborate techniques, because they can occur
arbitrarily nested in a tree. Current state-of-the-art approaches to solving
deep priority conflicts come with a severe performance overhead.
**Grounding** We evaluated our new approach against state-of-the-art
declarative disambiguation mechanisms. By parsing a corpus of popular
open-source repositories written in Java and OCaml, we found that our approach
yields speedups of up to 1.73x over a grammar rewriting technique when parsing
programs with deep priority conflicts--with a modest overhead of 1-2 % when
parsing programs without deep conflicts.
**Importance** A recent empirical study shows that deep priority conflicts
are indeed wide-spread in real-world programs. The study shows that in a corpus
of popular OCaml projects on Github, up to 17 % of the source files contain
deep priority conflicts. However, there is no solution in the literature that
addresses efficient disambiguation of deep priority conflicts, with support for
modular and composable syntax definitions
The design and implementation of Object Grammars
An Object Grammar is a variation on traditional BNF grammars, where the notation is extended to support declarative bidirectional mappings between text and object graphs. The two directions for interpreting Object Grammars are parsing and formatting. Parsing transforms text into an object graph by recognizing syntactic features and creating the corresponding object structure. In the reverse direction, formatting recognizes object graph features and generates an appropriate textual presentation. The key to Object Grammars is the expressive power of the mapping, which decouples the syntactic structure from the graph structure. To handle graphs, Object Grammars support declarative annotations for resolving textual names that refer to arbitrary objects in the graph structure. Predicates on the semantic structure provide additional control over the mapping. Furthermore, Object Grammars are compositional so that languages may be defined in a modular fashion. We have implemented our approach to Object Grammars as one of the foundations of the Ens (o) over bar system and illustrate the utility of our approach by showing how it enables definition and composition of domain-specific languages (DSLs). (C) 2014 Elsevier B.V. All rights reserved.</p
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