Abstract
Systems that are not dependable and insecure may be rejected by their users. For many systems controlled by computer, the most important system property is the dependability of the system. For this reason in this paper, we propose a complete approach for dependability analysis. The proposed approach is based on optimization qualitative and quantitative for dependability analysis, qualitative optimization is based on causality relations between the events deduced from the Truth Table Method combined with Karnaugh Table for deriving minimal feared states, q uantitative optimization is based on Reduced Markov Graph this graph is directly composed by a minimal feared state deduced from the qualitative optimization , to avoid the problem of combinatorial explosion in the number of states in the Markov graph modelling. The representation of the Markov graph will be particularly interesting to study dependability.
Highlights
The migration from analogical to digital components in the systems controlled by computer has increased the complexity of the systems
Most of the critical failures are generated by the interactions between the sub-systems, implemented in different technologies, which is based on the disciplines of mechanical engineering, electrical engineering and information technology....the dependability analysis, one of the most important problems for modern systems typically intelligent systems such as system controlled by computers, becomes extremely difficult
In order to avoid the explosion combinatorial of states in Truth table (TT) we focus the search of the feared state on the part of the system that are interesting for dependability analysis, precisely is to make the Truth Table of the part of the system that leads to the feared state by exploring the all states that have a causal relation with the occurrence of the feared state, we convert the TT to the Karnaugh Table (KT) for deriving Minimal Feared State (MFS) and construct the Reduced Markov Graph (RMG)
Summary
The migration from analogical to digital components in the systems controlled by computer has increased the complexity of the systems. The advantage of Markov graphs lies in their ability to take into account the dependencies between components and the possibility to obtain various measurements from the same database modelling (Reliability, Availability, security...) Despite their conceptual simplicity and their ability to overcome some shortcomings of the conventional methods of dependability, Markov graph is quickly confronted to the problem of combinative explosion in the number of states if the system is complex [5], [15], [16], [17], because the modelling process involves the enumeration of all possible states and all transitions between these states.
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