A logistic software reliability model with Loglog fault detection rate

A logistic software reliability model with Loglog fault detection rate

연구 분야: Verification

학회: Iran Journal of Computer Science

Research on software reliability modeling is essential for improving software quality, reducing costs, and ensuring customer satisfaction in the ever-expanding digital landscape. To achieve the desired level of reliability in the testing phase, software reliability growth models (SRGMs) are used. The goal of this study is to develop a novel SRGM based on a hypothesis obtained from a logistic model. The logistic model is commonly used to describe the rate of change in the size of a population over time. According to this model, a population’s per capita growth rate declines as it approaches the carrying capacity, which is the population’s upper bound. Similarly, in the software testing process, the fault detection rate per fault in the software grows faster in the beginning and later decreases with testing time until the maximum fault content is discovered. Considering the fault detection rate based on a log–log distribution, the proposed model is constructed in an NHPP analytical framework. The model is compared to six existing reliability models using four different evaluation criteria. The findings are quite encouraging.