Recursion synthesis with unrealizability witnesses

Farzan, Azadeh; Lette, Danya; Nicolet, Victor

doi:10.1145/3519939.3523726

Cited by 16 publications

(1 citation statement)

References 31 publications

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“…Recent decidability results for synthesis of uninterpreted programs involved a reduction to emptiness of two-way tree automata [Krogmeier et al 2020]. Decision procedures for SyGuS problems in linear and conditional linear integer arithmetic [Farzan et al 2022;Hu et al 2020] used grammar flow analysis [Möncke and Wilhelm 1991] and an abstraction based on semi-linear sets.…”

Section: Related Workmentioning

confidence: 99%

Languages with Decidable Learning: A Meta-theorem

Krogmeier¹,

Madhusudan²

2023

Preprint

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We study expression learning problems with syntactic restrictions and introduce the class of finite-aspect checkable languages to characterize symbolic languages that admit decidable learning. The semantics of such languages can be defined using a bounded amount of auxiliary information, which we call semantic aspects, that is independent of expression size but depends on a fixed structure over which evaluation occurs. We introduce a generic programming language for expressing model-checking programs that work over expression syntax trees, and we give a meta-theorem that connects such programs for finite-aspect checkable languages to finite tree automata, which allows us to derive new decidable learning results and decision procedures for several expression learning problems by writing model-checking programs in the programming language.

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Section: Related Workmentioning

confidence: 99%

Languages with Decidable Learning: A Meta-theorem

Krogmeier¹,

Madhusudan²

2023

Preprint

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Condition Synthesis Realizability via Constrained Horn Clauses

Rothenberg

Grumberg

Vizel

et al. 2023

Lecture Notes in Computer Science

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Relational Synthesis of Recursive Programs via Constraint Annotated Tree Automata

Miltner,

Wang,

Chaudhuri

et al. 2024

Computer Aided Verification

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In this paper, we present a new synthesis method based on the novel concept of a constraint annotated tree automaton (CATA). A CATA is a variant of a finite tree automaton (FTA) where the acceptance of a term by the automaton is conditioned upon the logical satisfiability of a formula. In the context of program synthesis, CATAs allow the construction of a more precise version space than FTAs by ruling out programs that make inconsistent assumptions about the unknown semantics of functions under synthesis. We apply our proposed algorithm to synthesizing recursive (or mutually recursive) procedures from relational specifications and demonstrate that our method allows solving synthesis problems that are beyond the scope of existing approaches.

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Recursion synthesis with unrealizability witnesses

Cited by 16 publications

References 31 publications

Languages with Decidable Learning: A Meta-theorem

Languages with Decidable Learning: A Meta-theorem

Condition Synthesis Realizability via Constrained Horn Clauses

Relational Synthesis of Recursive Programs via Constraint Annotated Tree Automata

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