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XLMC0202501 Topic 21 Quiz

Multiple choice

Consider the following undirected graph:        Which of the following node sequences are depth-first traversals of this graph that start at node D?  (check all that apply)

Options
A.DIFAJEKBHGC
B.DIFAEKBHGCJ
C.DEKGBHCIJFA
D.DJCGKEAFIBH
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To determine which sequences could be depth-first traversals (DFS) starting at D, we must follow the rule that DFS visits a node, then recursively explores one unvisited neighbor as deep as possible before backtracking to explore other unvisited neighbors. Option 1: DIFAJEKBHGC - Start at D: OK. - Next is I: this implies we chose I as the first neighbor to explore from D. If I has an unvisited path that goes as deep as possible before backtracking, we would traverse from I to F (as listed next), continuing to extend depth. - Then F: from I to F is a plausible deep step since F is adjacent to I and has further unvisited neighbors (e.g., A). The sequence goes F then A, which continues the deep dive. - Then A: moving from F to A is consistent with exploring a still-unvisited neighbor of F, and A would lead to E as the next deeper step (A → E is a valid edge). - Then J: after reaching E, choosing J as the next unvisited neighbor is plausible if J is a neighbor of E and not yet visited. This keeps the traversal going deeper along the E–J path before backtracking. - Then E: returning to E (we’re backtracking to explore other unvisit......Login to view full explanation

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DFS_Graph_4 Context: This question pertains to the use of the Graph Abstract Data Type (ADT) implemented with an Adjacency Map, as studied in our course. Instructions: Begin the traversal at Vertex 'A'. When selecting the next vertex to visit, adhere to alphabetical order. Question: Complete the depth-first search (DFS) for the graph shown below. Guidelines: Initiate the traversal at Vertex 'A', and proceed with the exploration, selecting vertices in alphabetical order where multiple paths are available. def DFS(g, u, discovered):    for e in g.incident_edges(u):        v = e.opposite(u)        if v not in discovered:            discovered[v] = e  # mark v as discovered via edge e            DFS(g, v, discovered)

DFS_Pse_2 This question pertains to the use of the Graph Abstract Data Type (ADT) implemented using an adjacency map, as studied in our course. The algorithms DFS and BFS are used to explore graphs but follow different strategies for traversal. Below is a simplified pseudocode version of a Depth-First Search (DFS) algorithm that uses recursion and a discovereddictionary to track visited vertices: DFS(Graph G, Vertex u, Map discovered):    for each edge e incident to u in G:        let v be the vertex opposite u on edge e        if v is not in discovered:            discovered[v] ← e     // edge e discovered v            DFS(G, v, discovered) In the DFS pseudocode, what does the discovered[v] ← e assignment represent? Graph ADT For reference: class Vertex:    def __init__(self, x):        self._element = x class Edge:    def __init__(self, u, v, x):        self._origin = u        self._destination = v        self._element = x     def opposite(self, v):        return self._destination if v == self._origin else self._origin class Graph:    def __init__(self, directed=False):        self._outgoing = {}        self._incoming = {} if directed else self._outgoing     def incident_edges(self, v):        return self._outgoing[v].values()

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