Analysis of Some Software Reliability Growth Models Using Failure Data of Real Time Control System

A newly developed software system is subjected to vigorous testing before its deployment. Testing aims at minimizing the probability of occurrence of failures. The aim of testing process is to build confidence in the software for its use in real world applications. Thus, reliability of systems is always an important issue for us. Growth in reliability takes place as the error detection and correction process is employed on the software. In order to model reliability growth, many formulations called as Software Reliability Growth Models (SRGMs) have been proposed that include some SRGMs based on Non-Homogeneous Poisson Process (NHPP). The role of human learning and experiential pattern gains are being studied and incorporated in such models. The realistic assumptions about human learning behavior and experiential gains of new skill-sets for better detection and correction of faults on software are being incorporated and studied in such models. In this paper, an analysis of some select SRGMs with learning effects is presented based on use of failure data of real time control system. Moreover, model comparisons on the basis of total defects predicted by the select models are also presented.