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

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Page 334

They do not retain any state information, and the

the input. They can be specified by giving the input and

procedures can be systematically derived using the approach developed by ...

They do not retain any state information, and the

**output**is purely dependent onthe input. They can be specified by giving the input and

**output**assertions. Libraryprocedures can be systematically derived using the approach developed by ...

Page 339

Further, assume that D is the degree of the computation, M is the potential input

volume and t < D < M . The worst possible case is when the computation is

correct for only D input values. Hence, Prob {

...

Further, assume that D is the degree of the computation, M is the potential input

volume and t < D < M . The worst possible case is when the computation is

correct for only D input values. Hence, Prob {

**output**of E is incorrectly computed}...

Page 340

The steps for computing CC(E, i-th

computer word length is infinite and that the expression can be proved (say, by

using ...

The steps for computing CC(E, i-th

**output**quantity) are: i) Obtain a symbolic**output**expression for each externally observable quantity. ii) Assuming that thecomputer word length is infinite and that the expression can be proved (say, by

using ...

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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