An optimal statistical testing policy for software reliability demonstration of safety-critical systems

When software reliability demonstration of safety-critical systems by statistical testing is treated as a Test, Analyse and Fix (TAAF) process, an optimal testing policy can be found, which maximises the probability of success of the whole process, over a pre-determined period of time. The optimisation problem is formulated, solved by stochastic dynamic programming, and demonstrated by two numerical examples

Reliability demonstration for safety-critical systems

This paper suggests a new model for reliability demonstration of safety-critical systems, based on the TRW Software Reliability Theory. The paper describes the model; the test equipment required and test strategies based on the various constraints occurring during software development. The paper also compares a new testing method, Single Risk Sequential Testing (SRST), with the standard Probability Ratio Sequential Testing method (PRST), and concludes that: • SRST provides higher chances of success than PRST • SRST takes less time to complete than PRST • SRST satisfies the consumer risk criterion, whereas PRST provides a much smaller consumer risk than the requirement

An Assessment of PIER Electric Grid Research 2003-2014 White Paper

This white paper describes the circumstances in California around the turn of the 21st century that led the California Energy Commission (CEC) to direct additional Public Interest Energy Research funds to address critical electric grid issues, especially those arising from integrating high penetrations of variable renewable generation with the electric grid. It contains an assessment of the beneficial science and technology advances of the resultant portfolio of electric grid research projects administered under the direction of the CEC by a competitively selected contractor, the University of California’s California Institute for Energy and the Environment, from 2003-2014

Expert Elicitation for Reliable System Design

This paper reviews the role of expert judgement to support reliability assessments within the systems engineering design process. Generic design processes are described to give the context and a discussion is given about the nature of the reliability assessments required in the different systems engineering phases. It is argued that, as far as meeting reliability requirements is concerned, the whole design process is more akin to a statistical control process than to a straightforward statistical problem of assessing an unknown distribution. This leads to features of the expert judgement problem in the design context which are substantially different from those seen, for example, in risk assessment. In particular, the role of experts in problem structuring and in developing failure mitigation options is much more prominent, and there is a need to take into account the reliability potential for future mitigation measures downstream in the system life cycle. An overview is given of the stakeholders typically involved in large scale systems engineering design projects, and this is used to argue the need for methods that expose potential judgemental biases in order to generate analyses that can be said to provide rational consensus about uncertainties. Finally, a number of key points are developed with the aim of moving toward a framework that provides a holistic method for tracking reliability assessment through the design process.Comment: This paper commented in: [arXiv:0708.0285], [arXiv:0708.0287], [arXiv:0708.0288]. Rejoinder in [arXiv:0708.0293]. Published at http://dx.doi.org/10.1214/088342306000000510 in the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

Developing a distributed electronic health-record store for India

The DIGHT project is addressing the problem of building a scalable and highly available information store for the Electronic Health Records (EHRs) of the over one billion citizens of India

Computer trading and systemic risk: a nuclear perspective

Financial markets have evolved to become complex adaptive systems highly reliant on the communication speeds and processing power afforded by digital systems. Their failure could cause severe disruption to the provision of financial services and possibly the wider economy. In this study we consider whether a perspective from the nuclear industry can provide additional insights

Validation of Ultrahigh Dependability for Software-Based Systems

Modern society depends on computers for a number of critical tasks in which failure can have very high costs. As a consequence, high levels of dependability (reliability, safety, etc.) are required from such computers, including their software. Whenever a quantitative approach to risk is adopted, these requirements must be stated in quantitative terms, and a rigorous demonstration of their being attained is necessary. For software used in the most critical roles, such demonstrations are not usually supplied. The fact is that the dependability requirements often lie near the limit of the current state of the art, or beyond, in terms not only of the ability to satisfy them, but also, and more often, of the ability to demonstrate that they are satisfied in the individual operational products (validation). We discuss reasons why such demonstrations cannot usually be provided with the means available: reliability growth models, testing with stable reliability, structural dependability modelling, as well as more informal arguments based on good engineering practice. We state some rigorous arguments about the limits of what can be validated with each of such means. Combining evidence from these different sources would seem to raise the levels that can be validated; yet this improvement is not such as to solve the problem. It appears that engineering practice must take into account the fact that no solution exists, at present, for the validation of ultra-high dependability in systems relying on complex software