A NHPP based software reliability model and optimal release policy with logistic–exponential test coverage under imperfect debugging

Abstract

Software reliability models are used to estimate and predict the reliability, number of remaining faults, failure intensity, total software development cost, etc., of a software. Testing coverage is very important for both software developers and customers of software products. Testing converge is a measure that enables software developers to evaluate the quality of tested software and determine how much additional effort is needed to improve the reliability of the software. This paper proposes a software reliability growth model based on a non-homogeneous Poisson process (NHPP) that incorporates a logistic–exponential testing coverage function with imperfect debugging. The proposed model relates the test coverage to fault detection phenomena in debugging. Goodness-of-fit test of the proposed model is conducted using different criteria for two sets of software failure data. The proposed model is compared with other existing NHPP models. A software cost model incorporating testing coverage and an optimal release policy based on the number of remaining faults are developed.