The performance of a syntax-guided synthesis algorithm is highly dependent on the provision of a good syntactic template, or grammar. Provision of such a template is often left to the user to do manually, though in the absence of such a grammar, state-of-the-art solvers will provide their own default grammar, which is dependent on the signature of the target program to be sythesized. In this work, we speculate this default grammar could be improved upon substantially. We build sets of rules, or metagrammars, for constructing grammars, and perform a gradient descent over these metagrammars aiming to find a metagrammar which solves more benchmarks and on average faster. We show the resulting metagrammar enables CVC4 to solve 26% more benchmarks than the default grammar within a 300s time-out, and that metagrammars learnt from tens of benchmarks generalize to performance on 100s of benchmarks.

中文翻译：

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用于语法引导合成的元语法上的梯度下降

句法引导合成算法的性能高度依赖于提供良好的句法模板或文法。提供这样的模板通常留给用户手动完成，尽管在没有这样的语法的情况下，最先进的求解器将提供他们自己的默认语法，这取决于目标程序的签名被合成。在这项工作中，我们推测可以大幅改进这种默认语法。我们构建了一组规则或元语法，用于构建语法，并对这些元语法执行梯度下降，旨在找到一个元语法，它可以解决更多的基准测试并且平均速度更快。我们展示了生成的元语法使 CVC4 能够在 300 秒的超时内比默认语法多解决 26% 的基准测试，