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TOC Alert for Publication# 4124007 2018February 22<![CDATA[Reliability analysis of safety-critical and control systems: a state-of-the-art review]]>1211182127<![CDATA[Comparative analysis of soft computing techniques for predicting software effort based use case points]]>12119292334<![CDATA[Mobile agent-based regression test case generation using model and formal specifications]]>12130403446<![CDATA[Variance analysis of software ageing problems]]>t-test to analyse the performances of two regression algorithms: auto-regressive integrated moving average and artificial neuron network. In the experiments, they analyse the variance in two levels: operating system level and application level. They find the result that k is equal to ten for k-fold cross-validation is proper for resource consumption prediction, although the contribution to variance is almost same for the sensitivity of forecasted estimation loss in consideration of data partitioning process and the sensitivity of forecasted estimation loss in consideration of data sampling procedure.]]>12141482066