PERFORMANCE ASSESSMENT OF NHPP SOFTWARE RELIABILITY MODELS APPLYING PARETO-TYPE LIFETIME DISTRIBUTION PROPERTIES

This study compares and evaluates the performance of NHPP-based software reliability models that apply Pareto-type lifetime distribution characteristics and proposes the optimal model based on this analysis. To analyze software failure phenomena, failure time data were utilized, and the parameters of the proposed model were determined through the maximum likelihood estimation (MLE) method. Various analyses (including assessing model efficiency using MSE and , evaluating prediction accuracy against true values using the mean value function, measuring failure occurrence intensity using the intensity function, and assessing future reliability using the reliability function) demonstrated that the Lomax model exhibited the best performance. Therefore, this research provides new insights into the reliability performance of Pareto-type lifetime distributions, which have been underexplored in existing studies, and also offers fundamental reliability attribute data that software developers need in the early stages.