A unified approach for developing two‐dimensional software reliability model

Software testing can be defined as a process to detect faults in the totality and worth of developed computer software. Testing is very important in assuring the quality of the software by identifying faults in software, and possibly removing them. But testing of the software for a long time may not ensure a bug‐free software and high reliability. Optimum amount of code also needs to be covered to make sure that the software is of good quality. Testing time alone may not give the correct picture of the number of faults removed in the software. Therefore, to capture the combined effect of testing time and testing coverage, we propose two‐dimensional software reliability growth models. We have used Cobb‐Douglas production function to develop the two‐dimensional model, incorporating the effect of testing time and testing coverage on the number of faults removed in the software system. A unified approach has been followed using hazard rate function for developing the models. Various continuous failure distributions are used to derive the models. The models developed are validated on real data sets and are compared to each other using various statistical tools.