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D.3.3 ALGORITHMS FOR INCREMENTAL ... - SecureChange

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SDA(C) = {DA 2 , DA 4 , DA 8 , DA 10 }<br />

− Calculate the Max Belief and Residual Risk.<br />

Max Belief(C) = max{0.054, 0.048, 0.189, 0.168} = 0.189<br />

Residual Risk(C) = 1 – (1 – 0.946) + (1 – 0.952) + (1 – 0.811) + (1 – 0.832) = 0.541<br />

Similarly, we can compute the Max Belief and Residual Risk of all design alternatives<br />

as follows.<br />

Design Alternative (DA) MB RR Trail (T)<br />

DA 1 G 9 ,G 6 ,G 7 ,G 10 ,G 11 0.018 0.982 {⟨ro1,0},⟨ro2,0⟩}<br />

DA 2 G 9 ,G 6 ,G 7 ,G 11 ,G 15 0.054 0.946 {⟨ro1,0⟩,⟨ro2,1⟩}<br />

DA 3 G 9 ,G 6 ,G 7 ,G 10 ,G 11 ,G 15 ,G 16 ,G 17 0.054 0.946 {⟨ro1,0⟩,⟨ro2,1⟩}<br />

DA 4 G 9 ,G 6 ,G 7 ,G 10 ,G 11 , G 15 ,G 16 ,G 17 ,G 19 ,G 20 0.048 0.952 {⟨ro1,0⟩,⟨ro2,2⟩}<br />

DA 5 G 9 ,G 6 ,G 7 ,G 10 ,G 11 , G 15 ,G 16 ,G 17 ,G 19 ,G 21 0.048 0.952 {⟨ro1,0⟩,⟨ro2,2⟩}<br />

DA 6 G 9 ,G 6 ,G 7 ,G 11 ,G 15 ,G 16 ,G 17 ,G 19 ,G 20 ,G 21 0.048 0.952 {⟨ro1,0⟩,⟨ro2,2⟩}<br />

DA 7 G 9 ,G 12 ,G 6 ,G 7 ,G 10 ,G 11 0.063 0.937 {⟨ro1,1⟩,⟨ro2,0⟩}<br />

DA 8 G 9 ,G 12 ,G 6 ,G 7 ,G 11 ,G 15 0.189 0.811 {⟨ro1,1⟩,⟨ro2,1⟩}<br />

DA 9 G 9 ,G 12 ,G 6 ,G 7 ,G 11 ,G 15 ,G 16 ,G 17 0.189 0.811 {⟨ro1,1⟩,⟨ro2,1⟩}<br />

DA 10 G 9 ,G 12 ,G 6 ,G 7 ,G 11 ,G 15 ,G 16 ,G 17 ,G 19 ,G 20 0.168 0.832 {⟨ro1,1⟩,⟨ro2,2⟩}<br />

DA 11 G 9 ,G 12 ,G 6 ,G 7 ,G 11 ,G 15 ,G 16 ,G 17 ,G 19 ,G 21 0.168 0.832 {⟨ro1,1⟩,⟨ro2,2⟩}<br />

DA 12 G 9 ,G 12 ,G 6 ,G 7 ,G 11 ,G 15 ,G 16 ,G 17 ,G 19 ,G 20 ,G 21 0.168 0.832 {⟨ro1,1⟩,⟨ro2,2⟩}<br />

DA 13 G 9 ,G 13 ,G 6 ,G 7 ,G 10 ,G 11 0.063 0.937 {⟨ro1,1⟩,⟨ro2,0⟩}<br />

DA 14 G 9 ,G 13 ,G 6 ,G 7 ,G 11 ,G 15 0.189 0.811 {⟨ro1,1⟩,⟨ro2,1⟩}<br />

DA 15 G 9 ,G 13 ,G 6 ,G 7 ,G 11 ,G 15 ,G 16 ,G 17 0.189 0.811 {⟨ro1,1⟩,⟨ro2,1⟩}<br />

DA 16 G 9 ,G 13 ,G 6 ,G 7 ,G 11 ,G 15 ,G 16 ,G 17 ,G 19 ,G 20 0.168 0.832 {⟨ro1,1⟩,⟨ro2,2⟩}<br />

DA 17 G 9 ,G 13 ,G 6 ,G 7 ,G 11 ,G 15 ,G 16 ,G 17 ,G 19 ,G 21 0.168 0.832 {⟨ro1,1⟩,⟨ro2,2⟩}<br />

DA 18 G 9 ,G 13 ,G 6 ,G 7 ,G 11 ,G 15 ,G 16 ,G 17 ,G 19 ,G 20 ,G 21 0.168 0.832 {⟨ro1,1⟩,⟨ro2,2⟩}<br />

DA 19 G 9 ,G 12 ,G 13 ,G 6 ,G 7 ,G 10 ,G 11 0.069 0.931 {⟨ro1,2⟩,⟨ro2,0⟩}<br />

DA 20 G 9 ,G 12 ,G 13 ,G 6 ,G 7 ,G 11 ,G 15 0.207 0.793 {⟨ro1,2⟩,⟨ro2,1⟩}<br />

DA 21 G 9 ,G 12 ,G 13 ,G 6 ,G 7 ,G 11 ,G 15 ,G 16 ,G 17 0.207 0.793 {⟨ro1,2⟩,⟨ro2,1⟩}<br />

DA 22 G 9 ,G 12 ,G 13 ,G 6 ,G 7 ,G 11 ,G 15 ,G 16 ,G 17 ,G 19 ,G 20 0.184 0.816 {⟨ro1,2⟩,⟨ro2,2⟩}<br />

DA 23 G 9 ,G 12 ,G 13 ,G 6 ,G 7 ,G 11 ,G 15 ,G 16 ,G 17 ,G 19 ,G 21 0.184 0.816 {⟨ro1,2⟩,⟨ro2,2⟩}<br />

DA 24 G 9 ,G 12 ,G 13 ,G 6 ,G 7 ,G 11 ,G 15 ,G 16 ,G 17 ,G 19 ,G 20 ,G 21 0.184 0.816 {⟨ro1,2⟩,⟨ro2,2⟩}<br />

Table 5. The DAT of the root node of the hypergraph in Figure 11.<br />

<strong>D.3.3</strong> Algorithms for Incremental Requirements Models<br />

Evaluation and Transformation| version 1.19 | page 27/136

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