A Software Reliability Model Considering a Scale Parameter of the Uncertainty and a New Criterion

Abstract

It is becoming increasingly common for software to operate in various environments. However, even if the software performs well in the test phase, uncertain operating environments may cause new software failures. Traditional proposed software reliability models under uncertain operating environments suffer from the problem of being well-suited to special cases due to the large number of assumptions involved. To improve these problems, this study proposes a new software reliability model that assumes an uncertain operating environment. The new software reliability model is a model that minimizes assumptions and minimizes the number of parameters that make up the model, so that the model can be applied to general situations better than the traditional proposed software reliability models. In addition, various criteria based on the difference between the predicted and estimated values have been used in the past to demonstrate the superiority of the software reliability models. Also, we propose a new multi-criteria decision method that can simultaneously consider multiple goodness-of-fit criteria. The multi-criteria decision method using ranking is useful for comprehensive evaluation because it does not rely on individual criteria alone by ranking and weighting multiple criteria for the model. Based on this, 21 existing models are compared with the proposed model using two datasets, and the proposed model is found to be superior for both datasets using 15 criteria and the multi-criteria decision method using ranking.

Keywords

• non-homogeneous Poisson process (NHPP)
• uncertain operating environments
• software reliability model
• multi-criteria decision method using ranking (MCDMR)