## Proceedings of the International School of Physics "Enrico Fermi". |

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Page 203

under the IFR

These restrictions must be reflected in the prior joint distribution of the «, in order

to represent informed opinion. This may be accomplished by using a Dirichlet ...

under the IFR

**assumption**and (3.4) 0<tt,<tt,<...<«t<l under the DFR**assumption**.These restrictions must be reflected in the prior joint distribution of the «, in order

to represent informed opinion. This may be accomplished by using a Dirichlet ...

Page 300

The major

selected randomly and independently from the input domain according to the

operational distribution. This is a very strong

general, ...

The major

**assumption**of all software reliability growth models is: Inputs areselected randomly and independently from the input domain according to the

operational distribution. This is a very strong

**assumption**and will not hold ingeneral, ...

Page 326

The major

Inputs are selected randomly and independently from the input domain according

to the operational distribution. This is a very strong

in ...

The major

**assumption**of all software reliability growth models is:**Assumption**.Inputs are selected randomly and independently from the input domain according

to the operational distribution. This is a very strong

**assumption**and will not holdin ...

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### Contents

System Eeliabujty | 3 |

Statistical Theory of Eeliablitt | 8 |

Definitions and characterizations | 12 |

Copyright | |

39 other sections not shown

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### Common terms and phrases

algorithm approach associated assume assumption Bayesian boundary points chain coherent system complex conjugate prior consider correctness defined denote detected discussed edited equations equivalence class ergodic errors example exponential distribution failure rate Fault Tree Analysis function gamma given human reliability IEEE Trans IFEA implementation increasing independent input domain integration interval likelihood Markov Markov chain matrix mean method modules monotone month2 N. D. Singpurwalla number of failures number of system NUMITEMS observed obtained operational output parameters phase Poisson Poisson process possible predictive prior distribution probability problem procedure Proschan R. E. Barlow random variables reliability growth models reliability theory renewal theory repair requirements sample sect sequence Software Eng software reliability software reliability models specification Stat statistical stochastic stochastic process subsection system failure system reliability techniques theorem tion tt tt values vector zero