The Bayesian reliability estimation under fuzzy environments is proposed in this paper. In order to apply the Bayesian approach, the fuzzy parameters are assumed to be fuzzy random variables with fuzzy prior distributions. The (conventional) Bayesian estimation method will be used to create the fuzzy Bayes point estimator of reliability by invoking the well-known theorem called ‘Resolution Iden...

Software reliability growth models only become useful if it is possible to estimate their parameters. However, the parameter estimation is normally done numerically, and hence a substantial amount of data is all too often needed. This need is often not fulfilled by modern development processes, for example incremental development and agile methods. This position paper identifies three alternati...

Complex technical systems may fail unexpectedly leading to process disruption and may bring a safety-hazard situation. The system failure is an outcome of failure dependency among subsystems where the degradation process of subsystems/components is random and uncertain process. Hence, reliability assessment of complex systems is of paramount importance. Quantitative reliability assessment needs...

Via Generalized Splitting Zdravko I. Botev, Pierre L’Ecuyer DIRO, Université de Montreal, C.P. 6128, Succ. Centre-Ville, Montréal (Québec), H3C 3J7, CANADA, {[email protected], [email protected]} Gerardo Rubino INRIA Rennes Bretagne Atlantique, Campus Universitaire de Beaulieu, 35042 Rennes Cedex, FRANCE, [email protected] Richard Simard DIRO, Université de Montreal, C.P. 6128...

OF THESIS ACCURATE SOFTWARE RELIABILITY ESTIMATION A large number of software reliability growth models are now available. It is widely known that none of these models performs well in all situations, and that choosing the appropriate model a priori is difficult. For this reason recent work has focused on how these models can be made more accurate, rather than trying to find a model which works...

Pattern classification techniques derived from statistical principles have been widely studied and have proven powerful in addressing practical classification problems. In real-world applications, the challenge is often to cope with unseen patterns i.e., patterns which are very different from those examined during the training phase. The issue with unseen patterns is the lack of accuracy of the...

Requirement for low operating and deployment costs of cellular networks motivate the need for self-organisation in cellular networks. To reduce operational costs, self-organising networks are fast becoming a necessity. One key issue in this context is self-organised coverage estimation that is done based on the signal strength measurement and reported position information of system users. In th...

In this paper we consider the issue of reliability of measurements in distributed adaptive estimation problem. To this aim, we assume a sensor network with different observation noise variance among the sensors and propose new estimation method based on incremental distributed least mean-square (IDLMS) algorithm. The proposed method contains two phases: I) Estimation of each sensors observation...

In confidence based reliability measurement we determine that we are nt least C confident that the probability of n program failing is less than or equal to c1 bound 8. The basic results of this approach are reviewed and several additional results introduced, including r/w adaptive sampling rheorem which shows how confidence can be computed when faults are correcred as they appear in the restin...

In many practical situations, one may be interested in knowing the extent to which the system will survive an interval of duration after it has been run for a long time. In such situation, the limiting interval reliability may be used as an appropriate measure for system effectiveness. Also, since it is difficult to obtain closed form expressions for the interval reliability, except for few sim...