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Conservative claims for the probability of perfection of a software-based system using operational experience of previous similar systems.

, , , , and . Reliab. Eng. Syst. Saf., (2018)

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Hardware and Software Dependability Evaluation: Software Dependability.. IFIP Congress, page 119. North-Holland/IFIP, (1989)Comments on 'Evolutionary neural network modelling for software cumulative failure time prediction' by Liang Tian and Afzel Noore Reliability Engineering and System Safety 87 (2005) 45-51.. Reliab. Eng. Syst. Saf., 91 (4): 485-486 (2006)Applying Bayesian Belief Networks to System Dependability Assessment., , and . SSS, page 71-94. Springer, (1996)Choosing Between Fault-Tolerance and Increased V&V for Improving Reliability., , and . PDPTA, CSREA Press, (2000)Conservative claims for the probability of perfection of a software-based system using operational experience of previous similar systems., , , , and . Reliab. Eng. Syst. Saf., (2018)On reliability assessment when a software-based system is replaced by a thought-to-be-better one., , , and . Reliab. Eng. Syst. Saf., (2020)Modeling the probability of failure on demand (pfd) of a 1-out-of-2 system in which one channel is "quasi-perfect"., , , , and . Reliab. Eng. Syst. Saf., (2017)A conservative bound for the probability of failure of a 1-out-of-2 protection system with one hardware-only and one software-based protection train., , , , , and . Reliab. Eng. Syst. Saf., (2014)Forecasting Software Reliability.. Software Reliability Modelling and Identification, volume 341 of Lecture Notes in Computer Science, page 141-206. Springer, (1987)E-voting: Dependability Requirements and Design for Dependability., , , and . ARES, page 988-995. IEEE Computer Society, (2006)