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We present novel formal structures, called named system states, that are specifically designed for modeling potentially underdetermined diagrams.
In general, there are many environmental conditions and system states that impact on the performance of a software system.
Both methods ensure to enclose the set of system states that is consistent with the model and the measurement noise bounds.
Such a map assigns to every set of apparatus states the set of system states that is compatible with the information that after the measurement interaction the apparatus is in one of these states.
When system states that used to reside in the healthy state move or transition to the marginal state, the system becomes stressed and the probability of the marginal state increases.
This consists in describing execution scenarios, expressed as regular expressions over the operations of the system, coupled with intermediate system states that have to be reached when the scenario is unfolded.
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An autonomic manager continuously monitors the managed system so as to detect any change in the system state that is in contrast to its objectives.
An error is part of the system state that is liable to lead to a failure (Avizienis et al. [2004]; Trivedi et al. [2010]).
The compensated level variable is a quickened display that provides estimates of system state that is not confounded by counter-intuitive and time-delayed thermodynamic effects.
Here we show that these reachability questions can be addressed through an "altitude function" analysis, in which we seek a scalar function of the system state that permits conclusions to be made regarding reachability without computing system trajectories.
In Appendix Two we develop an "altitude function" approach to this reachability problem, in which we seek a scalar function of the system state that permits conclusions to be made regarding reachability without computing system trajectories.
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