ON THE DEVELOPMENT OF UNIFIED SCHEME FOR DISCRETE SOFTWARE RELIABILITY GROWTH MODELING

The importance of Software Reliability Growth Models to control the testing process and for quantitative assessment of software reliability is a well established fact. However, difficulties created by their underlying assumptions, their relevance and validity to real testing environment have made the selection of appropriate model an uphill task. Recently, new dimensions have been added to software reliability engineering with the development of unified modeling schemes. These schemes have proved seminal in the development of the general theory, partially because of their simplicity and mathematical tractability. In this paper, we propose a unified scheme for discrete software reliability growth modeling using the fault detection/correction rate function. Standard probability distributions have been used to model the fault correction and detection times. Initially, we have formulated the unified scheme when the fault correction is immediate to the failure observation and later we extend it to the cases where removal is a two stage process namely failure observation followed by fault detection/correction. The use of fault detection/correction rate or else known as hazard rate to represent stage wise removal of fault during testing highlights the importance of the proposed framework. Convolution of probability distribution functions has been used to represent Stage-wise removal of fault i.e. failure observation, fault detection/fault correction. Few Discrete models have been derived using the proposed methodology. Parameter estimation on two real software failure datasets has been worked out. The results obtained are fairly accurate and quite encouraging.