It is widely recognized, by the scienti?c and technical community that m- surements are the bridge between the empiric world and that of the abstract concepts and knowledge. In fact, measurements provide us the quanti...
详细信息
ISBN:
(数字)9780387463285
ISBN:
(纸本)9780387306551;9781441940346
It is widely recognized, by the scienti?c and technical community that m- surements are the bridge between the empiric world and that of the abstract concepts and knowledge. In fact, measurements provide us the quantitative knowledge about things and phenomena. It is also widely recognized that the measurement result is capable of p- viding only incomplete information about the actual value of the measurand, that is, the quantity being measured. Therefore, a measurement result - comes useful, in any practicalsituation, only if a way is de?ned for estimating how incomplete is this information. The more recentdevelopment of measurement science has identi?ed in the uncertainty concept the most suitable way to quantify how incomplete is the information provided by a measurement result. However, the problem of how torepresentameasurementresulttogetherwithitsuncertaintyandpropagate measurementuncertaintyisstillanopentopicinthe?eldofmetrology,despite many contributions that have been published in the literature over the years. Many problems are in fact still unsolved, starting from the identi?cation of the best mathematical approach for representing incomplete knowledge. Currently, measurement uncertainty is treated in a purely probabilistic way, because the Theory of Probability has been considered the only available mathematical theory capable of handling incomplete information. However, this approach has the main drawback of requiring full compensation of any systematic e?ect that a?ects the measurement process. However, especially in many practical application, the identi?cation and compensation of all s- tematic e?ects is not always possible or cost e?ective.
Safety is a paradoxical system property. It remains immaterial, intangible and invisible until a failure, an accident or a catastrophy occurs and, too late, reveals its absence. And yet, a system cannot be relied upon...
详细信息
ISBN:
(数字)9781848003729
ISBN:
(纸本)9781848003712;9781849967945
Safety is a paradoxical system property. It remains immaterial, intangible and invisible until a failure, an accident or a catastrophy occurs and, too late, reveals its absence. And yet, a system cannot be relied upon unless its safety can be explained, demonstrated and certified. The practical and difficult questions which motivate this study concern the evidence and the arguments needed to justify the safety of a computer based system, or more generally its dependability. Dependability is a broad concept integrating properties such as safety, reliability, availability, maintainability and other related characteristics of the behaviour of a system in operation. How can we give the users the assurance that the system enjoys the required dependability? How should evidence be presented to certification bodies or regulatory authorities? What best practices should be applied? How should we decide whether there is enough evidence to justify the release of the system? To help answer these daunting questions, a method and a framework are proposed for the justification of the dependability of a computer-based system. The approach specifically aims at dealing with the difficulties raised by the validation of software. Hence, it should be of wide applicability despite being mainly based on the experience of assessing Nuclear Power Plant instrumentation and control systems important to safety. To be viable, a method must rest on a sound theoretical background.
暂无评论