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Automatic success tree-based reliability analysis for the consideration of transient and permanent faults

机译:基于成功树的自动可靠性分析,考虑瞬态和永久性故障

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摘要

Success tree analysis is a well-known method to quantify the dependability features of many systems. This paper presents a system-level methodology to automatically generate a success tree from a given embedded system implementation and subsequently analyzes its reliability based on a state-of-the-art Monte Carlo simulation. This enables the efficient analysis of transient as well as permanent faults while considering methods such as task and resource redundancy to compensate these. As a case study, the proposed technique is compared with two analysis techniques, successfully applied at system level: (1) a BDD-based reliability analysis technique and (2) a SAT-assisted approach, both suffering from exponential complexity in either space or time. Experimental results performed on an extensive test suite show that: (a) Opposed to the Success Tree (ST) and SAT-assisted approaches, the BDD-based approach is highly vulnerable to exhaust available memory during its construction for moderate and large test cases. (b) The proposed ST technique is competitive to the SAT-assisted analysis in analysis speed and accuracy, while being the only technique that is suitable to also handle large and complex system implementations in which permanent and transient faults may occur concurrently.
机译:成功树分析是一种量化许多系统的可靠性特征的众所周知的方法。本文提出了一种系统级方法,该方法可以从给定的嵌入式系统实现中自动生成成功树,并随后基于最新的蒙特卡洛模拟来分析其可靠性。这样就可以有效地分析瞬时故障和永久性故障,同时考虑使用诸如任务和资源冗余之类的方法来进行补偿。作为案例研究,将所提出的技术与两种分析技术进行了比较,两种分析技术已在系统级成功应用:(1)基于BDD的可靠性分析技术和(2)SAT辅助方法,它们在空间或空间中均面临指数复杂性时间。在广泛的测试套件上进行的实验结果表明:(a)与成功树(ST)和SAT辅助方法相反,基于BDD的方法在构造中型和大型测试用例的过程中极易耗尽可用内存。 (b)所提出的ST技术在分析速度和准确性上与SAT辅助分析相比具有竞争优势,同时它是唯一适用于处理可能同时发生永久性和暂态故障的大型复杂系统的唯一技术。

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