Model-based dependability analysis (original) (raw)
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Designing a dependable system successfully is a challenging issue that is an ongoing research subject in the literature. Different approaches have been adopted to analyse and verify the dependability of a system design. This process is far from obvious and often hampered due to the limitations of the classical dependability analysis and verification approaches. This paper provides an overview of model-based dependability analysis, design and verification approaches. Firstly, model-based analysis approaches are grouped by the limitations of the classical approaches. Secondly, design approaches have been classified looking at their underlying recovery strategies: hardware replication and hardware reuse. Then, the ins and outs of model-based verification approaches are identified starting from fault injection approaches towards their evolution into model-based integrative approaches. Finally, a model-based hybrid design process is presented making use of the reviewed analysis, design a...
Model-Based Dependability Analysis of Physical Systems with Modelica
Modelling and Simulation in Engineering
Modelica is an innovative, equation-based, and acausal language that allows modeling complex physical systems, which are made of mechanical, electrical, and electrotechnical components, and evaluates their design through simulation techniques. Unfortunately, the increasing complexity and accuracy of such physical systems require new, more powerful, and flexible tools and techniques for evaluating important system properties and, in particular, the dependability ones such as reliability, safety, and maintainability. In this context, the paper describes some extensions of the Modelica language to support the modeling of system requirements and their relationships. Such extensions enable the requirement verification analysis through native constructs in the Modelica language. Furthermore, they allow exporting a Modelica-based system design as a Bayesian Network in order to analyze its dependability by employing a probabilistic approach. The proposal is exemplified through a case study ...
A model-based method for system reliability analysis
System reliability is an important non-functional requirement whose satisfaction is even crucial for mission critical systems. However, the increase in both system complexity and accuracy required in the reliability analyses often makes inadequate traditional techniques which are mainly based on statistical and probabilistic tools and on the hierarchical decomposition of the system in terms of its components. Moreover, the integration of classical techniques in typical system development processes, and especially in the design phases, is quite difficult and thus their use is often postponed to the later development stages (e.g. system verification) with the possible risk of having to revise even basic design choices and with a consequent increase in both completion time and development cost. To address these issues, the paper proposes a Model-Based method for system reliability analysis which combines in a unified framework the benefits of popular OMG modeling languages (UML, SysML)...
Compositional dependability analysis of dynamic systems with uncertainty
Over the past two decades, research has focused on simplifying dependability analysis by looking at how we can synthesise dependability information from system models automatically. This has led to the field of model-based safety assessment (MBSA), which has attracted a significant amount of interest from industry, academia, and government agencies. Different model-based safety analysis methods, such as Hierarchically Performed Hazard Origin & Propagation Studies (HiP-HOPS), are increasingly applied by industry for dependability analysis of safety-critical systems. Such systems may feature multiple modes of operation where the behaviour of the systems and the interactions between system components can change according to what modes of operation the systems are in. MBSA techniques usually combine different classical safety analysis approaches to allow the analysts to perform safety analyses automatically or semi-automatically. For example, HiP-HOPS is a state-of-the-art MBSA approach which enhances an architectural model of a system with logical failure annotations to allow safety studies such as Fault Tree Analysis (FTA) and Failure Modes and Effects Analysis (FMEA). In this way it shows how the failure of a single component or combinations of failures of different components can lead to system failure. As systems are getting more complex and their behaviour becomes more dynamic, capturing this dynamic behaviour and the many possible interactions between the components is necessary to develop an accurate failure model. One of the ways of modelling this dynamic behaviour is with a state-transition diagram. Introducing a dynamic model compatible with the existing architectural information of systems can provide significant benefits in terms of accurate representation and expressiveness when analysing the dynamic behaviour of modern large-scale and complex safety-critical systems. Thus the first key contribution of this thesis is a methodology to enable MBSA techniques to model dynamic behaviour of systems. This thesis demonstrates the use of this methodology using the HiP-HOPS tool as an example, and thus extends HiP-HOPS with state-transition annotations. This extension allows HiP-HOPS to model more complex dynamic scenarios and perform compositional dynamic dependability analysis of complex systems by generating Pandora temporal fault trees (TFTs). As TFTs capture state, the techniques used for solving classical FTs are not suitable to solve them. They require a state space solution for quantification of probability. This thesis therefore proposes two methodologies based on Petri Nets and Bayesian Networks to provide state space solutions to Pandora TFTs. Uncertainty is another important (yet incomplete) area of MBSA: typical MBSA approaches are not capable of performing quantitative analysis under uncertainty. Therefore, in addition to the above contributions, this thesis proposes a fuzzy set theory based methodology to quantify Pandora temporal fault trees with uncertainty in failure data of components. The proposed methodologies are applied to a case study to demonstrate how they can be used in practice. Finally, the overall contributions of the thesis are evaluated by discussing the results produced and from these conclusions about the potential benefits of the new techniques are drawn.
A Model-Driven Dependability Analysis Method for Component-Based Architectures
2012
Critical distributed real-time embedded component-based systems must be dependable and thus be able to avoid unacceptable failures. To efficiently evaluate the dependability of the assembly obtained by selecting and composing components, well-integrated and tool-supported techniques are needed. Currently, no satisfying tool-supported technique fully integrated in the development life-cycle exists. To overcome this limitation, we propose CHESS-FLA, which is a model-driven failure logic analysis method. ...