Synthesis of Semantic Actions in Attribute Grammars

Attribute grammars allow the association of semantic actions to the production rules in context-free grammars, providing a simple yet effective formalism to define the semantics of a language. However, drafting the semantic actions can be tricky and a large drain on developer time. In this work, we...

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Published in:2022 Formal Methods in Computer-Aided Design (FMCAD) pp. 304 - 314
Main Authors: Kalita, Pankaj Kumar, Kumar, Miriyala Jeevan, Roy, Subhajit
Format: Conference Proceeding
Language:English
Published: FMCAD Association and authors 18.10.2022
Subjects:
Attribute grammar
C languages
Codes
Design automation
Java
Measurement
Production
Program synthesis
Semantic actions
Semantics
Syntax directed definition
ISSN:2708-7824
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Abstract Attribute grammars allow the association of semantic actions to the production rules in context-free grammars, providing a simple yet effective formalism to define the semantics of a language. However, drafting the semantic actions can be tricky and a large drain on developer time. In this work, we propose a synthesis methodology to automatically infer the semantic actions from a set of examples associating strings to their meanings. We also propose a new coverage metric, derivation coverage. We use it to build a sampler to effectively and automatically draw strings to drive the synthesis engine. We build our ideas into our tool, PĀNINI, and empirically evaluate it on twelve benchmarks, including a forward differentiation engine, an interpreter over a subset of Java bytecode, and a mini-compiler for C language to two-address code. Our results show that PĀNINI scales well with the number of actions to be synthesized and the size of the context-free grammar, significantly outperforming simple baselines.
AbstractList Attribute grammars allow the association of semantic actions to the production rules in context-free grammars, providing a simple yet effective formalism to define the semantics of a language. However, drafting the semantic actions can be tricky and a large drain on developer time. In this work, we propose a synthesis methodology to automatically infer the semantic actions from a set of examples associating strings to their meanings. We also propose a new coverage metric, derivation coverage. We use it to build a sampler to effectively and automatically draw strings to drive the synthesis engine. We build our ideas into our tool, PĀNINI, and empirically evaluate it on twelve benchmarks, including a forward differentiation engine, an interpreter over a subset of Java bytecode, and a mini-compiler for C language to two-address code. Our results show that PĀNINI scales well with the number of actions to be synthesized and the size of the context-free grammar, significantly outperforming simple baselines.
Author Kumar, Miriyala Jeevan
Roy, Subhajit
Kalita, Pankaj Kumar
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  organization: Indian Institute of Technology Kanpur,Computer Science and Engineering,Kanpur,India
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  givenname: Miriyala Jeevan
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  givenname: Subhajit
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  surname: Roy
  fullname: Roy, Subhajit
  email: subhajit@iitk.ac.in
  organization: Indian Institute of Technology Kanpur,Computer Science and Engineering,Kanpur,India
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Snippet Attribute grammars allow the association of semantic actions to the production rules in context-free grammars, providing a simple yet effective formalism to...
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StartPage 304
SubjectTerms Attribute grammar
C languages
Codes
Design automation
Java
Measurement
Production
Program synthesis
Semantic actions
Semantics
Syntax directed definition
Title Synthesis of Semantic Actions in Attribute Grammars
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