Recursive Program Synthesis from Sketches and Mixed-Quantifier Properties
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arXiv
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| Format: | Preprint |
| Published: |
2026
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| _version_ | 1866918276598071296 |
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| author | Egolf, Derek Tripakis, Stavros |
| author_facet | Egolf, Derek Tripakis, Stavros |
| contents | We present a novel approach to the automatic synthesis of recursive programs from mixed-quantifier first-order logic properties. Our approach uses Skolemization to reduce the mixed-quantifier synthesis problem to a $\forall^*$-synthesis problem, synthesizing witness-generating functions for introduced Skolem symbols alongside the target program. We tackle $\forall^*$-synthesis using a sketching-based, enumerative, counterexample-guided approach. Our algorithm learns syntactic constraints from counterexamples to prune the candidate space and employs a prophylactic pruning technique to avoid enumerating invalid candidates altogether. We evaluate our technique on 42 benchmarks, demonstrating that both counterexample generalization and prophylactic pruning significantly improve performance. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2601_04045 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Recursive Program Synthesis from Sketches and Mixed-Quantifier Properties Egolf, Derek Tripakis, Stavros Logic in Computer Science We present a novel approach to the automatic synthesis of recursive programs from mixed-quantifier first-order logic properties. Our approach uses Skolemization to reduce the mixed-quantifier synthesis problem to a $\forall^*$-synthesis problem, synthesizing witness-generating functions for introduced Skolem symbols alongside the target program. We tackle $\forall^*$-synthesis using a sketching-based, enumerative, counterexample-guided approach. Our algorithm learns syntactic constraints from counterexamples to prune the candidate space and employs a prophylactic pruning technique to avoid enumerating invalid candidates altogether. We evaluate our technique on 42 benchmarks, demonstrating that both counterexample generalization and prophylactic pruning significantly improve performance. |
| title | Recursive Program Synthesis from Sketches and Mixed-Quantifier Properties |
| topic | Logic in Computer Science |
| url | https://arxiv.org/abs/2601.04045 |