Software Reliability Growth Model with Varying- Time Fault Removal Efficiency As Well As With Fault Introduction

A large number of software reliability growth models have been proposed to analyze the reliability of software application during the testing phase, but none of the software reliability growth model is universal to all situations. However, most of the existing software reliability growth models are developed with the assumption that all the faults detected during the testing phase are removed, and no new fault is introduced in the debugging process. As far as this assumption is considered, it seems to be unrealistic in practical, therefore it is necessary to develop a software reliability growth models with assumption that new faults are introduced when the faults in the software system are corrected and removed during testing. This study develops a new software reliability growth model incorporating both fault removal efficiency as well as fault introduction. The study considered the sense that new faults can be introduced into the software during debugging and the detected faults may not be removed completely. The fault removal is not a simple process, because detected faults would be ambiguous to find and also consumes a lot of time to remove them successfully and also a numbers of procedures are involved. The procedures involved during the removal process are fault observation, fault position and fault modification. The applicability of proposed model is shown by validating it on software failure data sets obtained from different real software development projects. The comparisons with established models in terms of goodness of fit, the Akaike Information Criterion (AIC), Sum of Squared Errors (SSE), etc. have been presented. The proposed model is compared with the growth models available in the literature, and was found encouraging.