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

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Page 325

An error is easily

elements. Similarly, if it has a small size, then it is relatively more difficult to

the error. The size of an error depends on the way the inputs are selected.

An error is easily

**detected**if it has a large size since then it affects many inputelements. Similarly, if it has a small size, then it is relatively more difficult to

**detect**the error. The size of an error depends on the way the inputs are selected.

Page 328

This is clearly unsatisfactory since one would expect that errors which are

...

This is clearly unsatisfactory since one would expect that errors which are

**detected**later should have smaller (operational) error rates than those which are**detected**earlier. Littlewood [22] has developed a model where the failure rate of...

Page 329

This models the case where errors

sizes than those

models treat the program as a black box. That is, the reliability is estimated

without ...

This models the case where errors

**detected**later have (stochastically) smallersizes than those

**detected**earlier. 1*1.5. Applications. Software reliability growthmodels treat the program as a black box. That is, the reliability is estimated

without ...

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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