Abstract:

Mathematical model is basically a symbolic representation involving mathematical concepts/symbols and terminologies. Mathematical models are extremely powerful because they enable predictions to be made regarding a system. Further, these predictions provide a road map for further experimentation. Numerical models are utilized not just as a part of characteristic sciences and building disciplines but also in social sciences. Additionally, numerous physicists, engineers, analysts, financial experts, operations research examiners use scientific models most widely to pick the best strategy and test with the different alternative decisions. One of the fields where mathematical modeling has been vastly applied is reliability. The subject has been traditionally attached to hardware systems. Yet, with the expanding utilization of PCs in present times programming dependability has turned into a control in its own. Thus, making software reliability an important discipline in today’s era. The aim of this study is to the Software Reliability Engineering is an emerging discipline whose importance cannot be undermined. It is receiving unprecedented attention from researchers. In this thesis, it was endeavored to develop more practical resource allocation approach catering to different fault removal models under dynamic environment. The software reliability growth model based on Half Logistic order statistics distribution is framed. The software reliability growth models are framed based on Non-Homogeneous Poisson Process. Algorithms and MATLAB programs for these reliability growth models are developed. Modeling is a science which needs creativity linked with deep knowledge of the methods appearing in many fields like bio engineering, financial engineering, environment industry, information and communication technology, applied mathematics etc

Description:

Mathematical, Software Reliability Model, Numerical models, MATLAB programs