Software Reliability Modeling with Logistic Test Coverage Function

Test coverage is a good indicator for testing completeness and effectiveness, which has some effects on software reliability and defect coverage. Furthermore, the evaluation results of software reliability models with test coverage information will be further improved. Although some of traditional software reliability growth models have been widely applied to reliability prediction, it is likely that the prediction accuracy of these models can be further improved by adding other important factors affecting the final software reliability. Test coverage is believed to be one of such factors. Due to the integrated effects of software structure and learning factor on testing, test coverage increasing rate may exhibit a varying trend which first increases and then decreases. In other words, test coverage function may be an S-shaped curve which can be well and flexibly described by the Logistic function in many situations. Hence, this paper utilizes the Logistic function to describe the test coverage growth behavior. Based on this Logistic test coverage function, a defect prediction model that relates test coverage to fault detection is presented. Furthermore, combining NHPP modeling framework with Logistic test coverage function, a new software reliability model considering test coverage is proposed. Several case studies are also presented and analyzed. The results indicate that compared with several existing models, the new defect prediction model and reliability model considering Logistic test coverage function proposed in this paper can provide a substantial improvement in term of goodness-of-fit power and applicability.