We present semantic_induct, an automatic tool to recommend how to apply proof by induction in Isabelle/HOL. Given an inductive problem, semantic_induct produces candidate arguments to the induct tactic and selects promising ones using heuristics. Our evaluation based on 1,095 inductive problems from 22 theory files shows that semantic_induct achieves a 90.0\% increase of the coincidence rate for the most promising candidate within 5.0 seconds of timeout compared to an existing tool, smart_induct, while achieving a 62.0\% decrease of the median value of execution time.

中文翻译：

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Isabelle/HOL 中更快更智能的感应

我们提出了 Semantic_induct，这是一种自动工具，用于推荐如何在 Isabelle/HOL 中通过归纳应用证明。给定一个归纳问题，semantic_induct 为归纳策略生成候选参数，并使用启发式方法选择有希望的参数。我们基于 22 个理论文件中的 1,095 个归纳问题的评估表明，与现有工具 smart_induct 相比，semantic_induct 在超时 5.0 秒内将最有希望的候选者的符合率提高了 90.0%，同时降低了 62.0%执行时间的中值。