KSETKorean Society for Educational Technology
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We use the KNSSC algorithm to cluster KSet; then the set of clusters (CSet) can be gotten, in which different clusters represent the same pattern's different shapes.
Vulnerability incidents reported to KSET 2003 1.1% 2004 2.0% 2005 3.1% 2006 4.7% 2007 5.8% 2008 9.2% 2009 14.6% 2010 23.1% 2011 18.5% 2012 17.9% Note: Table made from bar graph.
We then use part of the state space (i.e., Figure 6(b)) to demonstrate the branches pruning effect of Ksets. Figure 7(a) shows the paths generated by the naive algorithm, while Figure 7(b) represents the results of the optimized algorithm which uses Ksets to prune superfluous paths.
Algorithm 1 implements the above discussed techniques, which takes as input a directed graph Reduced([DG.sub.P]), a set of basic faults BasicFaults, and bounded searching result Ksets. The output MCSList returns all minimal cut sets as a list, which will be initialized with Ksets.
For Reduced([DG.sub.RC]) in Figure 6, computing Ksets = {{Stuck}, {Bra_F}} with k = 1 firstly and then using Algorithm 1 to perform a full search in state space, we get all minimal cut sets MCSList = {{Stuck}, {Bra_F}}.
The role of Ksets will gradually change with the increasing of fc.
Input: Reduced(DG), BasicFaults, Ksets Output: MCSList is a list of minimal cut sets.