Packrat Parsing Research Articles

Packrat Parsing with Dynamic Buffer Allocation

Packrat parsing is a type of recursive decent parsing with guaranteed liner time parsing. For this,memoization technique is implemented in which all parsing results are memorized to avoid repetitive scanningof inputs in case of backtracking. The issue with this technique is large heap consumption for memoization whichout weigh the benefits. In many situations the developers need to make a tough decision of not implementingpackrat parsing despite the possibility of exponential time parsing. In this paper we present our developedtechnique to avoid such a tough choice. The heap consumption is upper bounded since memorized results arestored in buffer, capacity of which is decided at runtime depending on memory available in the machine. Thisdynamic buffer allocation is implemented by us in Mouse parser. This implementation achieves stableperformance against a variety of inputs with backtracking activities while utilizing appropriate size of memoryfor heap.

Parsing Expression Grammar and Packrat Parsing – A Review

Bryan Ford presented Parsing Expression Grammars (PEGs) as an alternative to specify rules for programming language, along with a Packrat parser, based on an idea of memoization. The idea proposed by B. Ford guarantees parsing of grammar written using PEGs in linear time in spite of backtracking. The primary aim of the paper is to highlight the details of PEGs followed by various challenges existing for a better understanding of the readers. From the entire overview presented, it has been observed that PEGs address the issue of undesired ambiguity in grammar for computer-oriented programming language, by not allowing any ambiguity in rules itself at the first place. However, the guarantee of linear time execution comes with a cost of large heap consumption, making it infeasible to implement for large inputs. Optimizing the resources required for memoization, may allow us to utilize the benefits offered by PEGs.

Implementation of C Library for Constructing Packrat Parser with Statically Allocated Memory

Implementation of C Library for Constructing Packrat Parser with Statically Allocated Memory

Packrat Parsing: A Literature Review

Packrat parsing is recently introduced technique based upon expression grammar. This parsing approach uses memoization and ensures a guarantee of linear parse time by avoiding redundant function calls by using memoization. This paper studies the progress made in packrat parsing till date and discusses the approaches to tackle this parsing process efficiently. In addition to this, other issues such as left recursion, error reporting also seems to be associated with this type of parsing approach and discussed here the efforts attempted by researchers to address this issue. This paper, therefore, presents a state of the art review of packrat parsing so that researchers can use this for further development of technology in an efficient manner.

Fast, Flexible, and Declarative Construction of Abstract Syntax Trees with PEGs

We address a declarative construction of abstract syntax trees with Parsing Expression Grammars. AST operators (constructor, connector, and tagging) are newly defined to specify flexible AST constructions. A new challenge coming with PEGs is the consistency management of ASTs in backtracking and packrat parsing. We make the transaction AST machine in order to perform AST operations in the context of the speculative parsing of PEGs. All the consistency control is automated by the analysis of AST operators. The proposed approach is implemented in the Nez parser, written in Java. The performance study shows that the transactional AST machine requires 25\% approximately more time in CSV, XML, and C grammars.

Arpeggio: A flexible PEG parser for Python

Arpeggio is a recursive descent parser with full backtracking and memoization based on PEG (Parsing Expression Grammar) grammars. This category of parsers is known as packrat parsers. It is implemented in the Python programming language and works as a grammar interpreter.Arpeggio has a very good support for error reporting, debugging, and grammar and parse tree visualization. It is used in industrial environments and teaching Domain-Specific Languages course at the Faculty of Technical Sciences in Novi Sad. Arpeggio is a foundation of a high-level DSL meta-language and tool - textX.It is a free and open-source software available at GitHub under MIT license.

Towards semantic mathematical editing

Currently, there exists a big gap between formal computer-understandable mathematics and informal mathematics, as written by humans. When looking more closely, there are two important subproblems: making documents written by humans at least syntactically understandable for computers, and the formal verification of the actual mathematics in the documents. In this paper, we will focus on the first problem.For the time being, most authors use ▪, ▪, or one of its graphical front-ends in order to write documents with many mathematical formulas. In the past decade, we have developed an alternative wysiwyg system GNU ▪, which is not based on ▪. All these systems are only adequate for visual typesetting and do not carry much semantics. Stated in the MathML jargon, they concentrate on presentation markup, not content markup.In recent versions of ▪, we have started to integrate facilities for the semantic editing of formulas. In this paper, we will describe these facilities and expand on the underlying motivation and design choices.To go short, we continue to allow the user to enter formulas in a visually oriented way. In the background, we continuously run a packrat parser, which attempts to convert (potentially incomplete) formulas into content markup. As long as all formulas remain sufficiently correct, the editor can then operate both on a visual or semantic level, independently of the low-level representation being used.An important related topic, which will also be discussed at length, is the automatic correction of syntax errors in existing mathematical documents. In particular, the syntax corrector that we have implemented enables us to upgrade existing documents and test our parsing grammar on various books and papers from different sources. We will provide a detailed analysis of these experiments.

The formalization and implementation of Adaptable Parsing Expression Grammars

The term “extensible language” is especially used when a language allows the extension of its own concrete syntax and the definition of the semantics of new constructs. Most popular tools designed for automatic generation of syntactic analysers do not offer any adequate resources for the specification of extensible languages. When used in the implementation of features like syntax macro definitions, these tools usually impose severe restrictions. For example, it may be required that macro definitions and their use reside in different files; or it may be impossible to perform the syntax analysis in one single pass. We claim that one of the main reasons for these limitations is the lack of appropriate formal models for the definition of the syntax of extensible languages.This paper presents the design and formal definition of Adaptable Parsing Expression Grammars, an extension to the Parsing Expression Grammar (PEG) model that allows the manipulation of its own production rules during the analysis of an input string. The proposed model compares favourably with similar approaches for the definition of the syntax of extensible languages. An implementation of the model is also presented, simulating the behaviour of packrat parsers. Among the challenges for this implementation is the use of attributes and on the fly modifications on the production rules at parse time, features not present in standard PEG. This approach has been used on the definition of a real extensible language, and initial performance tests suggest that the model may work well in practice.

Effective interactive proofs for higher-order imperative programs

We present a new approach for constructing and verifying higher-order, imperative programs using the Coq proof assistant. We build on the past work on the Ynot system, which is based on Hoare Type Theory. That original system was a proof of concept, where every program verification was accomplished via laborious manual proofs, with much code devoted to uninteresting low-level details. In this paper, we present a re-implementation of Ynot which makes it possible to implement fully-verified, higher-order imperative programs with reasonable proof burden. At the same time, our new system is implemented entirely in Coq source files, showcasing the versatility of that proof assistant as a platform for research on language design and verification. Both versions of the system have been evaluated with case studies in the verification of imperative data structures, such as hash tables with higher-order iterators. The verification burden in our new system is reduced by at least an order of magnitude compared to the old system, by replacing manual proof with automation. The core of the automation is a simplification procedure for implications in higher-order separation logic, with hooks that allow programmers to add domain-specific simplification rules. We argue for the effectiveness of our infrastructure by verifying a number of data structures and a packrat parser, and we compare to similar efforts within other projects. Compared to competing approaches to data structure verification, our system includes much less code that must be trusted; namely, about a hundred lines of Coq code defining a program logic. All of our theorems and decision procedures have or build machine-checkable correctness proofs from first principles, removing opportunities for tool bugs to create faulty verifications.

Parsing Expression Grammar as a Primitive Recursive-Descent Parser with Backtracking

Two recent developments in the field of formal languages are Parsing Expression Grammar (PEG) and packrat parsing. The PEG formalism is similar to BNF, but defines syntax in terms of recognizing st...

Better extensibility through modular syntax

We explore how to make the benefits of modularity available for syntactic specifications and present Rats! , a parser generator for Java that supports easily extensible syntax. Our parser generator builds on recent research on parsing expression grammars (PEGs), which, by being closed under composition, prioritizing choices, supporting unlimited lookahead, and integrating lexing and parsing, offer an attractive alternative to context-free grammars. PEGs are implemented by so-called packrat parsers, which are recursive descent parsers that memoize all intermediate results (hence their name). Memoization ensures linear-time performance in the presence of unlimited lookahead, but also results in an essentially lazy, functional parsing technique. In this paper, we explore how to leverage PEGs and packrat parsers as the foundation for extensible syntax. In particular, we show how make packrat parsing more widely applicable by implementing this lazy, functional technique in a strict, imperative language, while also generating better performing parsers through aggressive optimizations. Next, we develop a module system for organizing, modifying, and composing large-scale syntactic specifications. Finally, we describe a new technique for managing (global) parsing state in functional parsers. Our experimental evaluation demonstrates that the resulting parser generator succeeds at providing extensible syntax. In particular, Rats! enables other grammar writers to realize real-world language extensions in little time and code, and it generates parsers that consistently out-perform parsers created by two GLR parser generators.

Packrat parsing:

Packrat parsing is a novel technique for implementing parsers in a lazy functional programming language. A packrat parser provides the power and flexibility of top-down parsing with backtracking and unlimited lookahead, but nevertheless guarantees linear parse time. Any language defined by an LL( k ) or LR( k ) grammar can be recognized by a packrat parser, in addition to many languages that conventional linear-time algorithms do not support. This additional power simplifies the handling of common syntactic idioms such as the widespread but troublesome longest-match rule, enables the use of sophisticated disambiguation strategies such as syntactic and semantic predicates, provides better grammar composition properties, and allows lexical analysis to be integrated seamlessly into parsing. Yet despite its power, packrat parsing shares the same simplicity and elegance as recursive descent parsing; in fact converting a backtracking recursive descent parser into a linear-time packrat parser often involves only a fairly straightforward structural change. This paper describes packrat parsing informally with emphasis on its use in practical applications, and explores its advantages and disadvantages with respect to the more conventional alternatives.