Formal foundations for semi-parsing

Zaytsev, Vadim

doi:10.1109/csmr-wcre.2014.6747184

Cited by 7 publications

(12 citation statements)

References 35 publications

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“…• Used notation-parametric recovery [Zay12] and semiparsing [Zay14] to extract initial data ready for manual curation.…”

Section: Main Challenges and Approachesmentioning

confidence: 99%

Modelling of Language Syntax and Semantics: The Case of the Assembler Compiler.

Zaytsev¹

2020

JOT

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Application of software language technologies, whether analytical, transformational, or generational, in an industrial context is usually a taxing endeavour, with high demands in qualification levels of developers involved in it. Yet, if applied successfully, in the right places and with the right amount of effort, they promise high returns in terms of optimisation, effectiveness, validity and verifiability. In this paper, we report on our experience on writing a compiler for a complex second generation legacy programming language originally intended to be used on a mainframe. The business case for this product deals with companies migrating their software systems off the mainframe to cloud native or PC. Leveraging the documentation, available domain knowledge, several sample projects and a test suite, as well as several proprietary DSLs, we successfully modelled syntax and semantics of hundreds of instructions of that language, to the point of producing a compiler with a very limited group of compiler developers in limited time. The compiler is currently deployed at some of our customers and has received a top technology award from Microsoft.This report is meant to serve as a sample snapshot of how compilers can be built in the industry with software language engineering techniques. Traditional problems of compiler construction such as parsing or code optimisation either did not present a noticeable challenge or did not manifest themselves altogether in the course of this project, but MDE matters such as model transformation, modular design, the use of DSLs and meta-tools, were a constant concern. The focus of the report is in truthful representation of the domain as well as the details of the project, on reflection of the choices that were taken or could have been taken in the meantime, and on lessons learnt during the project.

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“…• Used notation-parametric recovery [Zay12] and semiparsing [Zay14] to extract initial data ready for manual curation.…”

Section: Main Challenges and Approachesmentioning

confidence: 99%

Modelling of Language Syntax and Semantics: The Case of the Assembler Compiler.

Zaytsev¹

2020

JOT

Self Cite

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“…The limitations of defining methodWater and classWater by hand illustrate the general problems of semi-parsing [8,9] with island grammars:…”

Section: An Advanced Island Grammarmentioning

confidence: 99%

“…PetitParser [3,11] is a PEG-based parser combinator [5] framework utilizing scannerless parsing [12] and packrat parsing [13]. Implementations of Petit-Parser exist for Pharo Smalltalk 8 (the version we extended), Java 9 and Dart. PPParser subclass : # PPSequence " Sequence of two parsers , p1 and p2 " instanceVariables : ' p1 p2 '. "…”

Section: Petitparser Internalsmentioning

confidence: 99%

Bounded seas

Kurs

Lungu

Iyadurai

et al. 2015

Computer Languages, Systems & Structures

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Imprecise manipulation of source code (semi-parsing) is useful for tasks such as robust parsing, error recovery, lexical analysis, and rapid development of parsers for data extraction. An island grammar precisely defines only a subset of a language syntax (islands), while the rest of the syntax (water) is defined imprecisely. Usually water is defined as the negation of islands. Albeit simple, such a definition of water is naive and impedes composition of islands. When developing an island grammar, sooner or later a language engineer has to create water tailored to each individual island. Such an approach is fragile, because water can change with any change of a grammar. It is time-consuming, because water is defined manually by an engineer and not automatically. Finally, an island surrounded by water cannot be reused because water has to be defined for every grammar individually. In this paper we propose a new technique of island parsing-bounded seas. Bounded seas are composable, robust, reusable and easy to use because island-specific water is created automatically. Our work focuses on applications of island parsing to data extraction from source code. We have integrated bounded seas into a parser combinator framework as a demonstration of their composability and reusability.

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“…Moreover, our research is not limited to dictionary lenses of Bohannon et al [13], since it concerns Final BX (Def. 4) and allows to continue expanding the bidirectional view on semiparsing methods [47], especially Lex Ast mappings that are entirely avoided in the current state of the art.…”

Section: Related Workmentioning

confidence: 99%

Parsing in a Broad Sense

Zaytsev

Bagge

2014

Lecture Notes in Computer Science

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Having multiple representations of the same instance is common in software language engineering: models can be visualised as graphs, edited as text, serialised as XML. When mappings between such representations are considered, terms "parsing" and "unparsing" are often used with incompatible meanings and varying sets of underlying assumptions. We investigate 12 classes of artefacts found in software language processing, present a case study demonstrating their implementations and state-of-the-art mappings among them, and systematically explore the technical research space of bidirectional mappings to build on top of the existing body of work and discover as of yet unused relationships.

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Formal foundations for semi-parsing

Cited by 7 publications

References 35 publications

Modelling of Language Syntax and Semantics: The Case of the Assembler Compiler.

Modelling of Language Syntax and Semantics: The Case of the Assembler Compiler.

Bounded seas

Parsing in a Broad Sense

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