Abstract
Number of software Reliability growth models has been proposed in the literature. A mathematical technique which describes the software testing phenomenon known as the software reliability growth model. Software reliability growth models are used to predict the number of faults and reliability of the software. In the view of this software reliability growth models are basically differentiated as the continuous and discrete models. There is a plenty of development in the continuous models but little towards the discrete models. In this paper we have presented a discrete reliability growth model with different discrete testing effort functions and the same time software release policy is discussed. A new imperfect debugging discrete software reliability growth model with testing effort is proposed. All calculations are done on real data. The results shows the proposed testing effort models are perfectly fit to the data.
Highlights
Software plays an important role in every body’s life
In this paper we proposed perfect and imperfect debugging testing effort dependent discrete software reliability growth model
4.1 Discrete software reliability growth model with Discrete TEF based on NHPP
Summary
Software plays an important role in every body’s life. From the general usages to the heavy equipment needs the software. Software reliability growth models [5][9] which were described as mathematical formulation of complex expressions which describes the real time testing environment These SRGM provides the mathematical relation between time span and cumulative faults which are discovered during the testing. Process models which considers the failure count data for reliability estimation and time interval process models which requires the time interval data These software reliability growth models are divided as two groups one based on calendar/execution time period and another based on the number of test cases used. In this paper we proposed perfect and imperfect debugging testing effort dependent discrete software reliability growth model. A) Discrete exponential curve: let W(n) be denote the expected cumulative number of faults detected up to nth testing-period. C) Discrete Logistic TEF : let L(n) be denote the expected cumulative number of faults detected up to nth testing-period. The parameter m is defined as e 1 + m × −α×t
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