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I was trying to implement an algorithm which finds the strongly connected components (SCC's) of a directed graph. In order to find the SCC's, as the last step we need to be able to generate the Depth-First Search Forest as mentioned in CLRS:

STRONGLY-CONNECTED-COMPONENTS (G)

 1. Call DFS(G) to compute finishing times f[u] for all u.
 2. Compute G^T
 3. Call DFS(G^T), but in the main loop, consider vertices in order of decreasing f[u] (as computed in first DFS)
 4. Output the vertices in each tree of the depth-first forest formed in second DFS as a separate SCC.

However, I did not understand how to generate the DFS Forests from the Depth First Search. Please explain me how is it possible, and preferably use Cormen's DFS Psuedocode as I am a beginner and am quite familiar with CLRS.

Below is Cormen's DFS psuedocode:

DFS (V, E)

1.     for each vertex u in V[G]
2.        do color[u] ← WHITE
3.                π[u] ← NIL
4.     time ← 0
5.     for each vertex u in V[G]
6.        do if color[u] ← WHITE
7.                then DFS-Visit(u)              ▷ build a new DFS-tree from u



DFS-Visit(u)

1.     color[u] ← GRAY                         ▷ discover u
2.     time ← time + 1
3.     d[u] ← time
4.     for each vertex v adjacent to u     ▷ explore (u, v)
5.        do if color[v] ← WHITE
6.                then π[v] ← u
7.                        DFS-Visit(v)
8.     color[u] ← BLACK
9.     time ← time + 1
10.   f[u] ← time                                 ▷ we are done with u

PS: Rest assured, this is not homework.

hengxin
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Danish A. Alvi
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1 Answers1

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Algorithm DFS-Visit(u) finds a tree that consists of vertices that are in the same connected component as vertex u. Basically, when you run DFS-Visit(u), you visit every vertex in the same connected component as u and you change their color to black.

In algorithm DFS(V, E), in steps 5-7, you find a vertex u with color white (which means that it is not in any of the previous trees/visited connected components) and run DFS-Visit(u) in order to find the next tree.

orezvani
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