摘要
软件故障已经成为导致系统出错、失效甚至崩溃的潜在与重要根源。因此,故障诊断技术对于保证软件质量具有非常重要的意义。基于人工智能理论的故障诊断技术已经得到越来越多的关注。贝叶斯网理论具有表述方便、推理严密等优点,将其与软件失效模式及影响分析方法相结合,提出了具有四层网络结构(原因层、模式层、故障层以及观察层)的WCMF贝叶斯网诊断模型。在此基础上,提出了基于故障信息数据库及诊断数据库的智能化软件故障诊断框架。最后,针对某数传导航机载软件进行了实例应用。结果表明,提出的WCMF诊断模型及诊断框架是可行且有效的,具有故障诊断方便及时、充分利用历史信息以提高诊断效率、降低时间和资源消耗等优点。
Software faults are the underlying and important roots which result in the mistake,failure and even breakdown of system.Therefore,the fault diagnosis technology is very significant to software quality assurance.Recently,the fault diagnosis technology based on the artificial intelligence theory attracts more and more attention.Because Bayesian networks theory has some significant advantages,such as easy expression and precise reasoning,a software fault diagnosis model with four layers（namely,reason,mode,fault and watch,short for WCMF） was firstly proposed by combining Bayesian networks with SFMEA（Software Failure Modes and Effect Analysis）.Secondly,a software fault diagnosis framework based on the fault information database and the fault diagnosis database was presented.Finally,a case study on navigation software was proposed.The results shown that the fault diagnosis model and presented framework is feasible and effective,which have the following advantages,such as timely and convenient fault diagnosis,improving diagnosis efficiency by utilizing the history information of the faults and their diagnosis.
出处
《计算机科学》
CSCD
北大核心
2010年第9期131-134,共4页
Computer Science
基金
国防技术基础项目"基于软件FTA/FMEA的故障诊断技术研究"(2132007B002)资助
