In recent years, the interest in probabilistic real-time has grown, as a response to the limitations of traditional static Worst-Case Execution Time (WCET) methods, in performing timing analysis of applications running on complex systems, like multi/many-cores and COTS platforms. The probabilistic theory can partially solve this problem, but it requires strong guarantees on the execution time traces, in order to provide safe probabilistic-WCET estimations. These requirements can be verified through suitable statistical tests, as described in this paper. In this work, we identify also challenges and problems of using statistical testing procedures in probabilistic real-time computing, proposing a unified test procedure based on a single index called Probabilistic Predictability Index (PPI). An experimental campaign has been carried out, considering both synthetic and realistic datasets, and the analysis of the impact of the Linux PREEMPT_RT patch on a modern complex platform as a use-case of the proposed index.

近年来，作为对传统静态最坏情况执行时间（WCET）方法的局限性的回应，对概率实时性的兴趣不断增长，它对运行在复杂系统（如多核/多核）上的应用程序进行时序分析和COTS平台。概率理论可以部分解决此问题，但它需要对执行时间轨迹进行有力的保证，以便提供安全的WCET概率估计。如本文所述，可以通过适当的统计检验来验证这些要求。在这项工作中，我们还确定了在概率实时计算中使用统计测试程序的挑战和问题，并提出了一个基于称为概率可预测性指数（PPI）的单一索引的统一测试程序。已经开展了一项实验性运动，