IMITATOR benchmarks library

IMITATOR benchmarks library是由洛林大学、CNRS、Inria和LORIA共同创建的数据集，包含56个基准测试案例，用于评估扩展参数时间自动机（PTAs）的新算法效率。数据集涵盖了学术和工业环境中的多种案例，包括活跃性属性、PTA扩展（如秒表或多速率时钟）以及无法解决的玩具基准。这些基准测试旨在强调现有参数综合技术的局限性，并鼓励未来开发新的专用算法。数据集的应用领域包括算法开发、模型评估和混合自动机的基准测试，旨在解决参数综合问题，特别是在早期设计阶段或运行时参数值未知的情况下。

The IMITATOR benchmarks library is a dataset co-created by the University of Lorraine, CNRS, Inria, and LORIA. It encompasses 56 benchmark cases for assessing the efficiency of novel algorithms for extended Parametric Timed Automata (PTAs). The dataset covers a diverse set of scenarios from both academic and industrial environments, including liveness properties, PTA extensions such as stopwatch or multi-rate clocks, and unsolvable toy benchmarks. These benchmarks are intended to highlight the limitations of current parameter synthesis technologies and foster the future development of new specialized algorithms. The application areas of this dataset include algorithm development, model evaluation, and hybrid automata benchmarking, with the goal of addressing parameter synthesis problems, particularly during the early design phase or when parameter values are unknown at runtime.