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

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Page 300

using

the change in

features ...

**growth models**may not be appropriate. The new**reliability**can be estimatedusing

**models**for the validation phase. However, it may be possible to estimatethe change in

**reliability**using fewer test cases by ensuring that the originalfeatures ...

Page 324

This method of estimating B is the basis of the Nelson model [4]. l'l. Software

and all errors which are detected are corrected. If we assume that no new errors

are ...

This method of estimating B is the basis of the Nelson model [4]. l'l. Software

**reliability growth models**. — During the debugging phase the software is testedand all errors which are detected are corrected. If we assume that no new errors

are ...

Page 427

learning is only loosely constrained. A third group of

assumptions about the general form of

experiences with ...

**reliability growth**is that it gives very little predictive capability, since futurelearning is only loosely constrained. A third group of

**models**requires strongassumptions about the general form of

**reliability growth**, based upon pastexperiences with ...

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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