Adaptive LL(*) parsing

ParrTerence,; HarwellSam,; FisherKathleen,

doi:10.1145/2714064.2660202

Cited by 31 publications

(22 citation statements)

References 19 publications

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“…Instead, there are many parser generators like Bison and Yacc [11] that take a grammar expressed in a domain-specific way, and generate code to parse that language. We are using ANTLR [12] [13] [14], It is a parser generator that uses LL(*) parsing [15] [16]. It takes a grammar as input and generates parsers that can build and walk parse trees and generate abstract syntax trees that can be further processed with tree parsers.…”

Section: Another Tool For Language Recognition (Antlr)mentioning

confidence: 99%

An Intermediate Representation-based Approach for Query Translation using a Syntax-Directed Method

Nassiri¹,

Machkour²,

Hachimi³

2020

IJACSA

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We aspire to make one query reasonably sufficient to extract data regardless of the data model used in our research. In such a way, users can freely use any query language they master to interrogate the heterogeneous database, not necessarily the query language associated with the model. Thus, overcoming the needing to deal with multiple query languages, which is, usually, an unwelcome matter for non-expert users and even for the expert ones. To do so, we proposed a new translation approach, relying on an intermediate query language to convert the user query into a suitable query language, according to the nature of data interrogated. Which is more beneficial rather than repeat the whole process for each new query submission. On the other hand, this empowers the system to be modular and divided into multiple, more flexible, and less complicated components. Therefore, it increases possibilities to make independent transformations and to switch between several query languages efficiently. By using our system, querying each data model with the corresponding query language is no longer bothersome. As a start, we are covering the eXtensible Markup Language (XML) and relational data models, whether native or hybrid. Users can retrieve data sources over these models using just one query, expressed with either the XML Path Language (XPath) or the Structured Query Language (SQL).

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Section: Another Tool For Language Recognition (Antlr)mentioning

confidence: 99%

An Intermediate Representation-based Approach for Query Translation using a Syntax-Directed Method

Nassiri¹,

Machkour²,

Hachimi³

2020

IJACSA

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“…The work presented in [36], where the authors present a method for document structure analysis with syntactic model and parsers for Japanese legal judgments, is closer to ours. In contrast with [36], our method does not rely on PEG [37] rules, but on CFG parser which allows for more flexibility in regards to ambiguity and context-dependent grammar by means of predicates [19].…”

Section: Legal Document Structuringmentioning

confidence: 99%

“…ANother Tool for Language Recognition (ANTLR), a language framework for constructing recognizers, interpreters, compilers and translators from grammatical descriptions containing actions in a variety of target languages, is among the most powerful and popular parser generators. ANTLR accepts as input any context-free grammar that does not contain indirect or hidden left-recursion and generates a lexer and a recursive-descent parser that uses an ALL(*) production prediction function [19]. Experiments presented in [19] have shown that ALL(*) outperforms general (Java) parsers by orders of magnitude, exhibiting linear time and space behavior for various languages.…”

mentioning

confidence: 99%

“…ANTLR accepts as input any context-free grammar that does not contain indirect or hidden left-recursion and generates a lexer and a recursive-descent parser that uses an ALL(*) production prediction function [19]. Experiments presented in [19] have shown that ALL(*) outperforms general (Java) parsers by orders of magnitude, exhibiting linear time and space behavior for various languages.…”

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confidence: 99%

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Solon: A Holistic Approach for Modelling, Managing and Mining Legal Sources

2018

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Recently there has been an exponential growth of the number of publicly available legal resources. Portals allowing users to search legal documents, through keyword queries, are now widespread. However, legal documents are mainly stored and offered in different sources and formats that do not facilitate semantic machine-readable techniques, thus making difficult for legal stakeholders to acquire, modify or interlink legal knowledge. In this paper, we describe Solon, a legal document management platform. It offers advanced modelling, managing and mining functions over legal sources, so as to facilitate access to legal knowledge. It utilizes a novel method for extracting semantic representations of legal sources from unstructured formats, such as PDF and HTML text files, interlinking and enhancing them with classification features. At the same time, utilizing the structure and specific features of legal sources, it provides refined search results. Finally, it allows users to connect and explore legal resources according to their individual needs. To demonstrate the applicability and usefulness of our approach, Solon has been successfully deployed in a public sector production environment, making Greek tax legislation easily accessible to the public. Opening up legislation in this way will help increase transparency and make governments more accountable to citizens.

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“…rather than its concrete syntactic structure. To create the AST, the code is first passed through a tool like ANTLR [15], which parses and builds a parse tree. Performing minimal modifications to the ANTLR parse tree creates an abstract syntax tree.…”

Section: Abstract Syntax Treementioning

confidence: 99%

Cloneless: Code Clone Detection via Program Dependence Graphs with Relaxed Constraints

Simko¹

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Code clones are pieces of code that have the same functionality. While some clones may structurally match one another, others may look drastically different. The inclusion of code clones clutters a code base, leading to increased costs through maintenance. Duplicate code is introduced through a variety of means, such as copy-pasting, code generated by tools, or developers unintentionally writing similar pieces of code. While manual clone identification may be more accurate than automated detection, it is infeasible due to the extensive size of many code bases. Software code clone detection methods have differing degree of success based on the analysis performed. This thesis outlines a method of detecting clones using a program dependence graph and subgraph isomorphism to identify similar subgraphs, ultimately illuminating clones. The project imposes few constraints when comparing code segments to potentially reveal more clones.

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Adaptive LL(*) parsing

Cited by 31 publications

References 19 publications

An Intermediate Representation-based Approach for Query Translation using a Syntax-Directed Method

An Intermediate Representation-based Approach for Query Translation using a Syntax-Directed Method

Solon: A Holistic Approach for Modelling, Managing and Mining Legal Sources

Cloneless: Code Clone Detection via Program Dependence Graphs with Relaxed Constraints

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