19,017 research outputs found
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
Safety Evaluation of Critical Applications Distributed on TDMA-Based Networks
Critical embedded systems have to provide a high level of dependability. In
automotive domain, for example, TDMA protocols are largely recommended because
of their deterministic behavior. Nevertheless, under the transient
environmental perturbations, the loss of communication cycles may occur with a
certain probability and, consequently, the system may fail. This paper analyzes
the impact of the transient perturbations (especially due to Electromagnetic
Interferences) on the dependability of systems distributed on TDMA-based
networks. The dependability of such system is modeled as that of
"consecutive-k-out-of-n:F" systems and we provide a efficient way for its
evaluation
Model-based dependability analysis : state-of-the-art, challenges and future outlook
Abstract: Over the past two decades, the study of model-based dependability analysis has gathered significant research interest. Different approaches have been developed to automate and address various limitations of classical dependability techniques to contend with the increasing complexity and challenges of modern safety-critical system. Two leading paradigms have emerged, one which constructs predictive system failure models from component failure models compositionally using the topology of the system. The other utilizes design models - typically state automata - to explore system behaviour through fault injection. This paper reviews a number of prominent techniques under these two paradigms, and provides an insight into their working mechanism, applicability, strengths and challenges, as well as recent developments within these fields. We also discuss the emerging trends on integrated approaches and advanced analysis capabilities. Lastly, we outline the future outlook for model-based dependability analysis
Software reliability and dependability: a roadmap
Shifting the focus from software reliability to user-centred measures of dependability in complete software-based systems. Influencing design practice to facilitate dependability assessment. Propagating awareness of dependability issues and the use of existing, useful methods. Injecting some rigour in the use of process-related evidence for dependability assessment. Better understanding issues of diversity and variation as drivers of dependability. Bev Littlewood is founder-Director of the Centre for Software Reliability, and Professor of Software Engineering at City University, London. Prof Littlewood has worked for many years on problems associated with the modelling and evaluation of the dependability of software-based systems; he has published many papers in international journals and conference proceedings and has edited several books. Much of this work has been carried out in collaborative projects, including the successful EC-funded projects SHIP, PDCS, PDCS2, DeVa. He has been employed as a consultant t
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Uncertainty explicit assessment of off-the-shelf software: Selection of an optimal diverse pair
Assessment of software COTS components is an essential part of component-based software development. Sub-optimal selection of components may lead to solutions with low quality. The assessment is based on incomplete knowledge about the COTS components themselves and other aspects, which may affect the choice such as the vendor's credentials, etc. We argue in favor of assessment methods in which uncertainty is explicitly represented (`uncertainty explicit' methods) using probability distributions. We have adapted a model (developed elsewhere by Littlewood, B. et al. (2000)) for assessment of a pair of COTS components to take account of the fault (bug) logs that might be available for the COTS components being assessed. We also provide empirical data from a study we have conducted with off-the-shelf database servers, which illustrate the use of the method
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Evaluation of software dependability
It has been said that the term software engineering is an aspiration not a description. We would like to be able to claim that we engineer software, in the same sense that we engineer an aero-engine, but most of us would agree that this is not currently an accurate description of our activities. My suspicion is that it never will be.
From the point of view of this essay â i.e. dependability evaluation â a major difference between software and other engineering artefacts is that the former is pure design. Its unreliability is always the result of design faults, which in turn arise as a result of human intellectual failures. The unreliability of hardware systems, on the other hand, has tended until recently to be dominated by random physical failures of components â the consequences of the âperversity of natureâ. Reliability theories have been developed over the years which have successfully allowed systems to be built to high reliability requirements, and the final system reliability to be evaluated accurately. Even for pure hardware systems, without software, however, the very success of these theories has more recently highlighted the importance of design faults in determining the overall reliability of the final product. The conventional hardware reliability theory does not address this problem at all.
In the case of software, there is no physical source of failures, and so none of the reliability theory developed for hardware is relevant. We need new theories that will allow us to achieve required dependability levels, and to evaluate the actual dependability that has been achieved, when the sources of the faults that ultimately result in failure are human intellectual failures
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Formalising Engineering Judgement on Software Dependability via Belief Networks
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The Law Commission presumption concerning the dependability of computer evidence
We consider the condition set out in section 69(1)(b) of the Police and Criminal Evidence Act 1984 (PACE 1984) that reliance on computer evidence should be subject to proof of its correctness, and compare it to the 1997 Law Commission recommendation that acommon law presumption be used that a computer operated correctly unless there is explicit evidence to the contrary (LC Presumption). We understand the LC Presumption prevails in current legal proceedings. We demonstrate that neither section 69(1)(b) of PACE 1984 nor the LC presumption reflects the reality of general software-based system behaviour
Aeronautical Engineering: A special bibliography with indexes, supplement 55
This bibliography lists 260 reports, articles, and other documents introduced into the NASA scientific and technical information system in February 1975
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