Software Reliability Growth Models Determining Release Time and Testing Effort using Exponentiated-Gompertz Method

Abstract

One important consideration for the software product is quality. Every stage of the software development process was done with the utmost attention to produce a high-quality output. The development process often incorporates a number of quantitative and qualitative methods. The final software product's features ought to meet every requirement. A crucial component that measures the likelihood that a software program will function before it genuinely fails to carry out its intended purpose is reliability. Software testing is a crucial stage that required enormous amounts of resources. This testing step required more than half of the budget, which is why it was conducted in a controlled setting. The critical point at which software product testing was terminated is thought to be the software product release time, and and it might be released onto the market, in which case the software product ought to be dependable and of high quality. In order to calculate the software release time, we used the exponentiated-gompertz function as the testing effort function in this paper's investigation of the idea of software testing effort dependent software reliability growth models. As a result, three genuine time datasets were used to compute the testing effort dependent models that were built. Least squares estimation is used to estimate parameters, and measures such as Mean Squared Error (MSE) and Absolute Error (AE) are used to compare models. The performance of the suggested testing effort dependant model outperformed that of the other models.