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arXiv 2102.00293cs.SE
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Using Bayesian Modelling to Predict Software Incidents

Chris Hobbs, Waqar Ahmed

英文摘要:

Traditionally, fault- or event-tree analyses or FMEAs have been used to estimate the probability of a safety-critical device creating a dangerous condition. However, these analysis techniques are less effective for systems primarily reliant on software, and are perhaps least effective in Safety of the Intended Functionality (SOTIF) environments, where the failure or dangerous situation occurs even though all components behaved as designed. This paper describes an approach we are considering at BlackBerry QNX: using Bayesian Belief Networks to predict defects in embedded software, and reports on early results from our research.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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