Abstract
In general, the software-testing time may be measured by two kinds of time scales: calendar time and test execution time. In this paper, we develop two-dimensional software reliability models with two-time measures and incorporate both of them to assess the software reliability with higher accuracy. Since the resulting software defect models are based on the familiar nonhomogeneous Poisson processes with two time scales, which are the natural extensions of one-dimensional software defect models, it is possible to treat the time data both simultaneously and effectively. We investigate the dependence of test-execution time as a testing effort on the software reliability assessment and validate quantitatively the software defect models with two-time scales. We also consider an optimization problem when to stop the software testing in terms of two-time measurements.
Highlights
The reliable software plays a central role to develop the dependable and high assurance computer-based systems
We investigate the dependence of test-execution time as a testing effort on the software reliability assessment and validate quantitatively our new Software defect models (SDMs) with two-time scales
We focus on two simplest cases where (T, S) obeys the bivariate exponential distribution by Marshall and Olkin (Marshall-Olkin distribution) [42, 43] and the bivariate Weibull distribution by Lu and Bhattacharyya [44], because the objective here is not to develop a number of SRMs with different fault-detection probabilities
Summary
The reliable software plays a central role to develop the dependable and high assurance computer-based systems. During the last three decades since the seminal contribution by Jelinski and Moranda [1], a huge number of SDMs have been extensively developed by many authors to help us in estimating the number of initial fault contents and understanding the effect of errors on software operation as well as in predicting the software reliability [2,3,4,5] These are characterized by modeling the software intensity function which implies the instantaneous debugging rate of software faults in the testing phase and is equivalent to the transition rate of stochastic point process. We consider an optimization problem when to stop the software testing in terms of two-time measurements
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