Reactive synthesis for the GR(1) fragment of LTL has been implemented and studied in many works. In this work we present and evaluate a list of heuristics to potentially reduce running times for GR(1) synthesis and related algorithms. The list includes several heuristics for controlled predecessor computation and BDDs, early detection of fixed-points and unrealizability, fixed-point recycling, and several heuristics for unrealizable core computations. We have implemented the heuristics and integrated them in our synthesis environment Spectra Tools, a set of tools for writing specifications and running synthesis and related analyses. We evaluate the presented heuristics on SYNTECH15, a total of 78 specifications of 6 autonomous Lego robots, on SYNTECH17, a total of 149 specifications of 5 autonomous Lego robots, all written by 3rd year undergraduate computer science students in two project classes we have taught, as well as on benchmarks from the literature. The evaluation investigates not only the potential of the suggested heuristics to improve computation times, but also the difference between existing benchmarks and the robot’s specifications in terms of the effectiveness of the heuristics. Our evaluation shows positive results for the application of all the heuristics together, which get more significant for specifications with slower original running times. It also shows differences in effectiveness when applied to different sets of specifications. Furthermore, a comparison between Spectra, with all the presented heuristics, and two existing tools, RATSY and Slugs, over two well-known benchmarks, shows that Spectra outperforms both on most of the specifications; the larger the specification, the faster Spectra becomes relative to the two other tools.

中文翻译：

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GR(1) 综合和相关算法的性能启发

LTL 的 GR(1) 片段的反应合成已在许多工作中实施和研究。在这项工作中，我们提出并评估了一系列启发式方法，以潜在地减少 GR(1) 合成和相关算法的运行时间。该列表包括用于受控前驱计算和 BDD 的几种启发式方法、定点和不可实现性的早期检测、定点回收以及用于无法实现的核心计算的几种启发式方法。我们已经实施了启发式方法并将它们集成到我们的综合环境 Spectra Tools 中，这是一组用于编写规范和运行综合及相关分析的工具。我们在 SYNTECH15 上评估了所提出的启发式，共有 6 个自主乐高机器人的 78 个规格，在 SYNTECH17 上，共有 5 个自主乐高机器人的 149 个规格，全部由计算机科学专业 3 年级本科生在我们教授的两个项目课程中以及基于文献的基准编写。评估不仅调查了建议的启发式方法在改进计算时间方面的潜力，而且还调查了现有基准和机器人在启发式方法有效性方面的规范之间的差异。我们的评估显示了将所有启发式方法一起应用的积极结果，这对于原始运行时间较慢的规范变得更加重要。当应用于不同的规范集时，它还显示了有效性的差异。此外，Spectra 与所有提供的启发式方法与两个现有工具 RATSY 和 Slugs 之间的比较，通过两个众所周知的基准测试，表明 Spectra 在大多数规格上都优于两者；规格越大，Spectra 相对于其他两个工具的速度就越快。