Recursive Program Synthesis from Sketches and Mixed-Quantifier Properties

Abstract

We present a novel approach for the synthesis of recursive programs from mixed-quantifier first-order logic properties. We solve this problem 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 implement our technique in a tool called Cataclyst and evaluate it on a suite of 60 benchmarks. We demonstrate that both counterexample generalization and prophylactic pruning significantly improve performance. Cataclyst solves 59/60 benchmarks, while variants of Cataclyst without counterexample generalization or prophylactic pruning solve fewer benchmarks. The only other tool that can handle mixed-quantifier specifications does not support sketching, so a direct comparison is not possible. This prior tool solves 12/60 benchmarks.