Synthesizing Formal Semantics from Executable Interpreters
Authors: 
Jiangyi Liu, Charlie Murphy, Anvay Grover, Keith J.C. Johnson, 
Thomas Reps, Loris D’AntoniAuthors Info & Claims
Jiangyi Liu, Charlie Murphy, Anvay Grover, Keith J.C. Johnson, Thomas Reps, Loris D’AntoniAuthors Info & ClaimsArticle No.: 284, Pages 362 - 388
Abstract
Program verification and synthesis frameworks that allow one to customize the language in which one is interested typically require the user to provide a formally defined semantics for the language. Because writing a formal semantics can be a daunting and error-prone task, this requirement stands in the way of such frameworks being adopted by non-expert users. We present an algorithm that can automatically synthesize inductively defined syntax-directed semantics when given (i) a grammar describing the syntax of a language and (ii) an executable (closed-box) interpreter for computing the semantics of programs in the language of the grammar. Our algorithm synthesizes the semantics in the form of Constrained-Horn Clauses (CHCs), a natural, extensible, and formal logical framework for specifying inductively defined relations that has recently received widespread adoption in program verification and synthesis. The key innovation of our synthesis algorithm is a Counterexample-Guided Synthesis (CEGIS) approach that breaks the hard problem of synthesizing a set of constrained Horn clauses into small, tractable expression-synthesis problems that can be dispatched to existing SyGuS synthesizers. Our tool Synantic synthesized inductively-defined formal semantics from 14 interpreters for languages used in program-synthesis applications. When synthesizing formal semantics for one of our benchmarks, Synantic unveiled an inconsistency in the semantics computed by the interpreter for a language of regular expressions; fixing the inconsistency resulted in a more efficient semantics and, for some cases, in a 1.2x speedup for a synthesizer solving synthesis problems over such a language.
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October 2024
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Published: 08 October 2024
Published in PACMPL Volume 8, Issue OOPSLA2
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