Analysis of Theoretical Sampling Distributed using combined LPETM and ANOM subgrouping

Kotte Sandeep*, R.Satya Prasad, K.Sowmya

A whole new software reliability technology is introduced that predicts expected failures as well or superior to anything existing software reliability models, which is simpler than any of the models that approach it in predictive legitimacy. The model consolidates both execution time and schedule time components, each one off and this can be inferred. The model is assessed using genuine information. Logarithmic Poisson Execution Time Model (LPETM) is a software reliability model which predicts the normal disappointments like failures and henceforth related reliability quantities superior to existing software models. It utilizes Non-Homogenous Poisson Process (NHPP) with a mean esteem work that is reliant on exponentially falling flaw recognition rate. The Maximum Likelihood (MLE) is an aspect devised to accurate the LPETM model’s required intriguing determinations. The Analysis of Means (ANOM) is the best graphical statistical techniques for contrasting group means to grand mean to uncover convincing contrasts among means which are generated through adopted LPETM. The model is evaluated by using Brazilian Electronic Switching System (BESS) for 1500 subscribers with 70 data entries and 100000 random percentiles generated by using Python programming.

Volume 11 | Issue 1

Pages: 467-471