Analysis of System-Failure Rate Caused by Soft-Errors using a UML-Based Systematic Methodology in an SoC

This paper proposes an analytical method to assess the soft-error rate (SER) in the early stages of a System-on-Chip (SoC) platform-based design methodology. The proposed method gets an executable UML (Unified Modeling Language) model of the SoC and the raw soft- error rate of different parts of the platform as its inputs. Soft-errors on the design are modeled by disturbances on the value of attributes in the classes of the UML model and disturbances on opcodes of software cores. The Dynamic behavior of each core is used to determine the propagation probability of each variable disturbance to the core outputs. Furthermore, the SER and the execution time of each core in the SoC and a Failure Modes and Effects Analysis (FMEA) that determines the severity of each failure mode in the SoC are used to compute the System-Failure Rate (SFR) of the So

Use of COTS functional analysis software as an IVHM design tool for detection and isolation of UAV fuel system faults

This paper presents a new approach to the development of health management solutions which can be applied to both new and legacy platforms during the conceptual design phase. The approach involves the qualitative functional modelling of a system in order to perform an Integrated Vehicle Health Management (IVHM) design – the placement of sensors and the diagnostic rules to be used in interrogating their output. The qualitative functional analysis was chosen as a route for early assessment of failures in complex systems. Functional models of system components are required for capturing the available system knowledge used during various stages of system and IVHM design. MADe™ (Maintenance Aware Design environment), a COTS software tool developed by PHM Technology, was used for the health management design. A model has been built incorporating the failure diagrams of five failure modes for five different components of a UAV fuel system. Thus an inherent health management solution for the system and the optimised sensor set solution have been defined. The automatically generated sensor set solution also contains a diagnostic rule set, which was validated on the fuel rig for different operation modes taking into account the predicted fault detection/isolation and ambiguity group coefficients. It was concluded that when using functional modelling, the IVHM design and the actual system design cannot be done in isolation. The functional approach requires permanent input from the system designer and reliability engineers in order to construct a functional model that will qualitatively represent the real system. In other words, the physical insight should not be isolated from the failure phenomena and the diagnostic analysis tools should be able to adequately capture the experience bases. This approach has been verified on a laboratory bench top test rig which can simulate a range of possible fuel system faults. The rig is fully instrumented in order to allow benchmarking of various sensing solution for fault detection/isolation that were identified using functional analysis

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

Diverse protection systems for improving security: a study with AntiVirus engines

Diverse “barriers” or “protection systems” are very common in many industries, especially in safety-critical ones where the designers must use “defense in depth” techniques to prevent safety failures. Similar techniques are also commonly prescribed for security systems: using multiple, diverse detection systems to prevent security breaches. However empirical evidence of the effectiveness of diversity is rare. We present results of an empirical study which uses a large-scale dataset to assess the benefits of diversity with an important category of security systems: AntiVirus products. The analysis was based on 1599 malware samples collected from a distributed honeypot deployment over a period of 178 days. The malware samples were sent to the signature engines of 32 different AntiVirus products hosted by the VirusTotal service. We also present an exploratory model which shows that the number of diverse protection layers that are needed to achieve “perfect” detection with our dataset follows an exponential power-law distribution. If this distribution is shown to be generic with other datasets, it would be a cost-effective means for predicting the probability of perfect detection for systems that use a large number of barriers based on measurements made with systems that are composed of fewer (say 2, 3) barriers

Addendum to Informatics for Health 2017: Advancing both science and practice

This article presents presentation and poster abstracts that were mistakenly omitted from the original publication

Beyond the golden run : evaluating the use of reference run models in fault injection analysis

Fault injection (FI) has been shown to be an effective approach to assess- ing the dependability of software systems. To determine the impact of faults injected during FI, a given oracle is needed. This oracle can take a variety of forms, however prominent oracles include (i) specifications, (ii) error detection mechanisms and (iii) golden runs. Focusing on golden runs, in this paper we show that there are classes of software which a golden run based approach can not be used to analyse. Specifically we demonstrate that a golden run based approach can not be used when analysing systems which employ a main control loop with an irregular period. Further, we show how a simple model, which has been refined using FI, can be employed as an oracle in the analysis of such a system