表示依赖关系的广义有向图模型

Pascal Fradet, Xiaojie Guo, J. Monin, Sophie Quinton
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引用次数: 9

摘要

在计算机辅助验证可调度性分析的背景下,非常有表现力的任务模型对于分解尽可能多的分析的正确性证明是有用的。有向图任务模型由于其强大的表达能力似乎是一个很好的候选。遗憾的是,它捕捉不同任务的作业的到达时间和执行时间之间的依赖关系的能力非常有限。针对有限抢占的固定优先级调度问题,提出了一个推广有向图模型的任务模型及其相应分析。一个任务可以生成几种类型的作业,每种作业都有自己的最坏情况执行时间、优先级、不可抢占段和最大抖动。我们在Coq证明助手中以一种适合其形式化的方式给出了分析的正确性证明。我们的目标(仍在进行中)是正式证明通用模型的分析,以便更具体(标准或新颖)分析的正确性证明归结为指定和证明其转换到我们的模型。此外,在一个共同框架中表达许多不同的分析为正式比较铺平了道路。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Generalized Digraph Model for Expressing Dependencies
In the context of computer assisted verification of schedulability analyses, very expressive task models are useful to factorize the correctness proofs of as many analyses as possible. The digraph task model seems a good candidate due to its powerful expressivity. Alas, its ability to capture dependencies between arrival and execution times of jobs of different tasks is very limited. We propose here a task model that generalizes the digraph model and its corresponding analysis for fixed-priority scheduling with limited preemption. A task may generate several types of jobs, each with its own worst-case execution time, priority, non-preemptable segments and maximum jitter. We present the correctness proof of the analysis in a way amenable to its formalization in the Coq proof assistant. Our objective (still in progress) is to formally certify the analysis for that general model such that the correctness proof of a more specific (standard or novel) analysis boils down to specifying and proving its translation into our model. Furthermore, expressing many different analyses in a common framework paves the way for formal comparisons.
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