Inferring Context-Free Grammars for Domain-Specific Languages | Zendy

Matej Črepinšek | Zendy; Marjan Mernik | Zendy; Barrett R. Bryant | Zendy; Faizan Javed | Zendy; Alan Sprague | Zendy

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Inferring Context-Free Grammars for Domain-Specific Languages

Author(s) -

Matej Črepinšek,

Marjan Mernik,

Barrett R. Bryant,

Faizan Javed,

Alan Sprague

Publication year - 2005

Publication title -

electronic notes in theoretical computer science

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.242

H-Index - 60

ISSN - 1571-0661

DOI - 10.1016/j.entcs.2005.02.055

Subject(s) - computer science , l attributed grammar , context free grammar , programming language , tree adjoining grammar , extended affix grammar , rule based machine translation , stochastic context free grammar , definite clause grammar , domain (mathematical analysis) , natural language processing , context sensitive grammar , grammar , fifth generation programming language , artificial intelligence , syntax , second generation programming language , adaptive grammar , affix grammar , programming paradigm , mathematics , linguistics , generative grammar , operator precedence grammar , mathematical analysis , philosophy

In the area of programming languages, context-free grammars (CFGs) are of special importance since almost all programming languages employ CFG's in their design. Recent approaches to CFG induction are not able to infer context-free grammars for general-purpose programming languages. In this paper it is shown that syntax of a small domain-specific language can be inferred from positive and negative programs provided by domain experts. In our work we are using the genetic programming approach in grammatical inference. Grammar-specific heuristic operators and nonrandom construction of the initial population are proposed to achieve this task. Suitability of the approach is shown by examples where underlying context-free grammars are successfully inferred

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