Probabilistic risk assessment framework for software propagation analysis of failures

Wei, Yuan; Rodrı́guez, Manuel; Smidts, Carol

doi:10.1243/1748006xjrr241

Cited by 5 publications

(11 citation statements)

References 41 publications

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“…Because these are likely contributors to software failures, systematic approaches that support these aspects of OP definition should be developed (e.g., see Wei et al [2010] for an approach to systematically analyze input failures for software used in safety critical applications typically studied in a risk-based framework, e.g., probabilistic risk assessment models).…”

Section: Discussion and Open Research Questionsmentioning

confidence: 99%

Software testing with an operational profile

et al. 2014

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This article is devoted to the survey, analysis, and classification of operational profiles (OP) that characterize the type and frequency of software inputs and are used in software testing techniques. The survey follows a mixed method based on systematic maps and qualitative analysis. This article is articulated around a main dimension, that is, OP classes, which are a characterization of the OP model and the basis for generating test cases. The classes are organized as a taxonomy composed of common OP features (e.g., profiles, structure, and scenarios), software boundaries (which define the scope of the OP), OP dependencies (such as those of the code or in the field of interest), and OP development (which specifies when and how an OP is developed). To facilitate understanding of the relationships between OP classes and their elements, a meta-model was developed that can be used to support OP standardization. Many open research questions related to OP definition and development are identified based on the survey and classification.

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Section: Discussion and Open Research Questionsmentioning

confidence: 99%

Software testing with an operational profile

et al. 2014

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“…The range of x over which equation (8) is satisfied gives the FP preserved. The total FP resulting from a differential operation can be determined using equation 1and rules 9 and 10.…”

Section: Advanced Arithmetic Operations and Fp Determinationmentioning

confidence: 99%

“…ISO/IEC/IEEE 24765:2010(E) 6 and Wei et al 8 9 calculation continues until the end of the program, till line 15. The FP at the end of the program is 6, inf ½ Þ.…”

Section: Application To a Complex Examplementioning

confidence: 99%

“…Then applying proposition 1 indicates that the FP total is ( À inf, À 8) [(1,5) [ (8, inf ). Furthermore, applying Lemma 1 results in a FP killed which corresponds to the interval (À 8, 1) [(5,8).…”

mentioning

confidence: 99%

“…FPs are generated upon multiplication of two functions, when one function is inversely proportional to the other. Rule 4 can be expressed as equation(8) …”

mentioning

confidence: 99%

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Basis for non-propagation domains, their transformations and their impact on software reliability

Mutha

Smidts

2017

Proceedings of the Institution of Mechanical Engineers, Part O:

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Fault propagation analysis is an important step in determining system reliability and defining fault tolerance strategies. Typically, in the early software design phases, the propagation probability for a fault is assumed to be one. However, the assumption that faults will always propagate highly underestimates reliability, and valuable resources may be wasted on fixing faults that may never propagate. To determine the fault propagation probability, a concept of flat parts is introduced. A flat part is a property of a function; when multiple functions containing flat parts interact with each other, these flat parts undergo a transformation. During this transformation, the flat parts may be killed, preserved, or new flat parts may be generated. Interval arithmetic-based rules to determine such flat part transformations are introduced. A flat part-based propagation analysis can be used to determine the reliability of a software system, or software-driven mechanical system expressed functionally. In addition, the information obtained through flat part-based propagation analysis can be used to add sensors within the flat parts to increase the probability of fault detection, thus increasing the robustness of the system under study.

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