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    潘庆和 洪炳熔. 软件故障优化注入方案研究与分析[J]. 计算机研究与发展, 2011, 48(3): 528-534.
    引用本文: 潘庆和 洪炳熔. 软件故障优化注入方案研究与分析[J]. 计算机研究与发展, 2011, 48(3): 528-534.
    Pan Qinghe and Hong Bingrong. Optimized Injecting Method of Software-Implemented Fault Injection Technique[J]. Journal of Computer Research and Development, 2011, 48(3): 528-534.
    Citation: Pan Qinghe and Hong Bingrong. Optimized Injecting Method of Software-Implemented Fault Injection Technique[J]. Journal of Computer Research and Development, 2011, 48(3): 528-534.

    软件故障优化注入方案研究与分析

    Optimized Injecting Method of Software-Implemented Fault Injection Technique

    • 摘要: 主要研究了基于空间注入技术的软件故障注入(software-implemented fault injection, SWIFI)实验与分析中存在的问题.提出了并设计了2种基于空间注入技术的注入方式:等待方式与冲击方式,分别设计了2种方式的注入算法,并利用它们分别进行了故障注入实验,通过实验着重分析了注入地址不同的空间分布对实验产生的影响.详细讨论并分析了基于不同空间地址概率分布的故障注入实验问题,根据实验结果得出并证明结论,针对空间注入技术实施的2种注入算法在执行软件故障注入实验时总存在一种相对较优的注入方案.

       

      Abstract: As an analysis method of software dependability, software-implemented fault injection (SWIFI) has been concerned and studied for a long time. Many injectors have been designed to implement injecting experiments. These injectors run on different platforms and have different test goals. In this paper, a software-implemented fault injector is designed to run on Windows NT platform. The aim is to test and evaluate reliability of software that will work in high-radiation environment. In such environment, SEU (single event upsets) is a main reason that causes failure of software. In our injector, SEU is emulated by flipping one-bit or multi-bits in memory or registers and memory injecting is the research focus. In order to perfect injecting theory and experimental technique, some related issues are studied in this paper. Based on memory space injecting technique, two injecting methods are designed and time complexity is computed respectively. Two kinds of injecting experiments are implemented according to these methods. Usually fault injecting experiment is time-consuming and ineffective, so it is important to choose an injecting plan that can optimize tests. The different distributions of location random variable X are used to implement experiments. Through comparative analysis of the experimental results, a conclusion is made that there is always an injecting plan that can significantly optimize experiments.

       

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