NHPP software reliability model considering the uncertainty of operating environments with imperfect debugging and testing coverage

• The uncertainty of operating environments and imperfect debugging are considered.• Fault detection rate is based on testing coverage and the model is based on NHPP.• The performance of the proposed model is compared with other 15 existing models.• Optimal software release time and its sensitivity...

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Vydáno v:Applied Mathematical Modelling Ročník 51; s. 68 - 85
Hlavní autoři: Li, Qiuying, Pham, Hoang
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York Elsevier Inc 01.11.2017
Elsevier BV
Témata:
Cost analysis
Criteria
Debugging
Fault detection
Goodness of fit
Imperfect debugging (ID)
Non-homogeneous Poisson process (NHPP)
Operating environment
Performance prediction
Poisson density functions
Reliability analysis
Sensitivity analysis
Software reliability
Software reliability growth models (SRGMs)
Studies
Testing coverage
Uncertainty
Non-homogeneous Poisson process (NHPP)
Imperfect debugging (ID)
Uncertainty
Testing coverage
Operating environment
Software reliability growth models (SRGMs)
ISSN:0307-904X, 1088-8691, 0307-904X
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Shrnutí:• The uncertainty of operating environments and imperfect debugging are considered.• Fault detection rate is based on testing coverage and the model is based on NHPP.• The performance of the proposed model is compared with other 15 existing models.• Optimal software release time and its sensitivity analysis are discussed based on cost and reliability.• Seven criteria and improved normalized criteria distance method are used in the experiments. In this paper, we propose a testing-coverage software reliability model that considers not only the imperfect debugging (ID) but also the uncertainty of operating environments based on a non-homogeneous Poisson process (NHPP). Software is usually tested in a given control environment, but it may be used in different operating environments by different users, which are unknown to the developers. Many NHPP software reliability growth models (SRGMs) have been developed to estimate the software reliability measures, but most of the underlying common assumptions of these models are that the operating environment is the same as the developing environment. But in fact, due to the unpredictability of the uncertainty in the operating environments for the software, environments may considerably influence the reliability and software's performance in an unpredictable way. So when a software system works in a field environment, its reliability is usually different from the theory reliability, and also from all its similar applications in other fields. In this paper, a new model is proposed with the consideration of the fault detection rate based on the testing coverage and examined to cover ID subject to the uncertainty of operating environments. We compare the performance of the proposed model with several existing NHPP SRGMs using three sets of real software failure data based on seven criteria. Improved normalized criteria distance (NCD) method is also used to rank and select the best model in the context of a set of goodness-of-fit criteria taken all together. All results demonstrate that the new model can give a significant improved goodness-of-fit and predictive performance. Finally, the optimal software release time based on cost and reliability requirement and its sensitivity analysis are discussed.
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ISSN:0307-904X
1088-8691
0307-904X
DOI:10.1016/j.apm.2017.06.034