Software reliability modeling using soft computing techniques

Abstract

Software engineering is the process of analyzing user requirements, newlinedesigning, implementation, testing and maintenance of the applications that newlinesatisfy the customer requirement. Software quality is the most important newlinething, since the success of a company and software engineers asset by the newlinedevelopment of failure free software. One of the most important quality factor newlineis reliability. Software engineering is incomplete without Software reliability. newlineSoftware Reliability is a process of providing failure-free solutions until the newlinelifetime of the software. Software reliability can improve through Software newlineReliability models, analyzing failure data, proper utilization of quality newlineassurance team and evaluating the results. newlineThe software reliability models provides information to predict failure, newlineunderstand the characteristics of how and why software fails, and try to newlinequantify software reliability. Hence design of suitable software reliability newlinemodel has a significant impact of predicting the failure of the software. An newlineimportant issue in software reliability modelling is to design a single model to newlineprocess different type of failure data sets which are aroused in different newlineenvironment. To overcome this issue various algorithms are considered in this newlineresearch work for designing a single suitable software reliability model to newlinedeal different type of failure data sets. newlineThe Seasonal ARIMA model is a sort of linear event (data) prediction newlinemodel for forecasting time-based events or data on the underlying data newlinegenerating method. Future events or results are projected in this model based newlineon the compilation of previous observations and values of past data newline