LOGISTIC REGRESSION APPROACH TO SOFTWARE RELIABILITY ENGINEERING WITH FAILURE PREDICTION

In this paper using the main feature of our proposed Model in its inflection point, we propose a software reliability growth model, which relatively early in the testing and debugging phase, provides accurate parameters estimation, gives a very good failure behavior prediction and enable software developers to predict when to conclude testing, release the software and avoid over testing in order to cut the cost during the development and the maintenance of the software. Two real world experimental data previously analyzed have been used to compare our proposed Early Estimation Logistic Model effectiveness with several pre-existing models.