题目
COMP9024-Data Structures and Algorithms - 2025 T1
单项选择题
Consider the graph above. In DFS, to search for a path from 5 to 1 (visiting nodes in an ascending order), what is the next node to visit after 4?
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思路分析
The prompt asks us to determine, in a DFS from node 5 to node 1 (visiting nodes in ascending order), what the next node to visit after 4 would be. However, the provided data is incomplete: the answer_options array is empty, and there is only a single listed answer "d. 4 is not......Login to view full explanation登录即可查看完整答案
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类似问题
The diagram below represents a problem using a search tree. Which of the following options shows the correct order of node visits to reach Wendy using Depth-First Search (DFS)?
How does depth-first search complete its search of the search tree?
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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