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.
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More From: International Journal of System Assurance Engineering and Management
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