22,707 research outputs found
Rigorously assessing software reliability and safety
This paper summarises the state of the art in the assessment of software reliability and safety ("dependability"), and describes some promising developments. A sound demonstration of very high dependability is still impossible before operation of the software; but research is finding ways to make rigorous assessment increasingly feasible. While refined mathematical techniques cannot take the place of factual knowledge, they can allow the decision-maker to draw more accurate conclusions from the knowledge that is available
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Assessing the Risk due to Software Faults: Estimates of Failure Rate versus Evidence of Perfection.
In the debate over the assessment of software reliability (or safety), as applied to critical software, two extreme positions can be discerned: the ‘statistical’ position, which requires that the claims of reliability be supported by statistical inference from realistic testing or operation, and the ‘perfectionist’ position, which requires convincing indications that the software is free from defects. These two positions naturally lead to requiring different kinds of supporting evidence, and actually to stating the dependability requirements in different ways, not allowing any direct comparison. There is often confusion about the relationship between statements about software failure rates and about software correctness, and about which evidence can support either kind of statement. This note clarifies the meaning of the two kinds of statement and how they relate to the probability of failure-free operation, and discusses their practical merits, especially for high required reliability or safety
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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Confidence: Its role in dependability cases for risk assessment
Society is increasingly requiring quantitative assessment of risk and associated dependability cases. Informally, a dependability case comprises some reasoning, based on assumptions and evidence, that supports a dependability claim at a particular level of confidence. In this paper we argue that a quantitative assessment of claim confidence is necessary for proper assessment of risk. We discuss the way in which confidence depends upon uncertainty about the underpinnings of the dependability case (truth of assumptions, correctness of reasoning, strength of evidence), and propose that probability is the appropriate measure of uncertainty. We discuss some of the obstacles to quantitative assessment of confidence (issues of composability of subsystem claims; of the multi-dimensional, multi-attribute nature of dependability claims; of the difficult role played by dependence between different kinds of evidence, assumptions, etc). We show that, even in simple cases, the confidence in a claim arising from a dependability case can be surprisingly low
The Art of Fault Injection
Classical greek philosopher considered the foremost virtues to be temperance, justice, courage, and prudence. In this paper we relate these cardinal virtues to the correct methodological approaches that researchers should follow when setting up a fault injection experiment. With this work we try to understand where the "straightforward pathway" lies, in order to highlight those common methodological errors that deeply influence the coherency and the meaningfulness of fault injection experiments. Fault injection is like an art, where the success of the experiments depends on a very delicate balance between modeling, creativity, statistics, and patience
The problems of assessing software reliability ...When you really need to depend on it
This paper looks at the ways in which the reliability of software can be assessed and predicted. It shows that the levels of reliability that can be claimed with scientific justification are relatively modest
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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 – i.e. dependability evaluation – 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 – the consequences of the ‘perversity of nature’. 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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On the use of testability measures for dependability assessment
Program “testability” is informally, the probability that a program will fail under test if it contains at least one fault. When a dependability assessment has to be derived from the observation of a series of failure free test executions (a common need for software subject to “ultra high reliability” requirements), measures of testability can-in theory-be used to draw inferences on program correctness. We rigorously investigate the concept of testability and its use in dependability assessment, criticizing, and improving on, previously published results. We give a general descriptive model of program execution and testing, on which the different measures of interest can be defined. We propose a more precise definition of program testability than that given by other authors, and discuss how to increase testing effectiveness without impairing program reliability in operation. We then study the mathematics of using testability to estimate, from test results: the probability of program correctness and the probability of failures. To derive the probability of program correctness, we use a Bayesian inference procedure and argue that this is more useful than deriving a classical “confidence level”. We also show that a high testability is not an unconditionally desirable property for a program. In particular, for programs complex enough that they are unlikely to be completely fault free, increasing testability may produce a program which will be less trustworthy, even after successful testin
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