Software Reliability Modeling with Test Coverage: Experimentation and Measurement with A Fault-Tolerant Software Project

As the key factor in software quality, software reliability quantifies software failures. Traditional software reliability growth models use the execution time during testing for reliability estimation. Although testing time is an important factor in reliability, it is likely that the prediction accuracy of such models can be further improved by adding other parameters which affect the final software quality. Meanwhile, in software testing, test coverage has been regarded as an indicator for testing completeness and effectiveness in the literature. In this paper, we propose a novel method to integrate time and test coverage measurements together to predict the reliability. The key idea is that failure detection is not only related to the time that the software experiences under testing, but also to what fraction of the code has been executed by the testing. This is the first time that execution time and test coverage are incorporated together into one single mathematical form to estimate the reliability achieved. We further extend this method to predict the reliability of fault- tolerant software systems. The experimental results with multi-version software show that our reliability model achieves a substantial estimation improvement compared with existing reliability models.