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The links between human error diversity and software diversity: Implications for fault diversity seeking

机译:人为错误多样性和软件多样性之间的联系:对故障多样性寻求的启示

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Software diversity is known to improve fault tolerance in N-version software systems by independent development. As the leading cause of software faults, human error is considered an important factor in diversity seeking. However, there is little scientific research focusing on how to seek software fault diversity based on human error mechanisms. A literature review was conducted to extract factors that may differentiate people with respect to human error-proneness. In addition, we constructed a conceptual model of the links between human error diversity and software diversity. An experiment was designed to validate the hypotheses, in the form of a programming contest, accompanied by a survey of cognitive styles and personality traits. One hundred ninety-two programs were submitted for the identical problem, and 70 surveys were collected. Code inspection revealed 23 faults, of which 10 were coincident faults. The results show that personality traits seems not effective predictors for fault diversity as a whole model, whereas cognitive styles and program measurements moderately account for the variation of fault density. The results also show causal relations between performance levels and coincident faults: coincident faults are unlikely to occur at skill-based performance level; the coincident faults introduced in rule-based performances show a high probability of occurrence, and the coincident faults introduced in knowledge-based performances are shaped by the content and formats of the task itself. Based on these results, we have proposed a model to seek software diversity and prevent coincident faults.
机译:通过独立开发,已知软件多样性可提高N版本软件系统的容错能力。作为软件故障的主要原因,人为错误被认为是寻求多样性的重要因素。但是,很少有科学研究集中在如何基于人为错误机制寻求软件故障多样性上。进行了文献综述以提取可能在人为错误倾向方面使人与众不同的因素。此外,我们构建了人为错误多样性与软件多样性之间联系的概念模型。设计了一个实验,以编程竞赛的形式验证假设,并伴随对认知风格和人格特质的调查。针对同一问题提交了192个程序,并收集了70个调查。代码检查发现23个故障,其中10个是巧合故障。结果表明,人格特质似乎不是故障多样性作为一个整体模型的有效预测指标,而认知方式和程序测量适度说明了故障密度的变化。结果还显示了绩效水平与巧合错误之间的因果关系:巧合错误不太可能发生在基于技能的绩效水平上;基于规则的性能中引入的重合故障显示出很高的可能性,而基于知识的性能中引入的重合故障则受任务本身的内容和格式的影响。基于这些结果,我们提出了一个模型来寻求软件的多样性并防止同时发生的故障。

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