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Comparing Depth-First and Breadth-First Search Algorithms in Graph Traversal

This article explores the traversal processes of Depth-First Search (DFS) and Breadth-First Search (BFS) algorithms, focusing on their application in graph theory. We demonstrate DFS using a stack to explore reachable vertices from a start point, processing nodes in a depth-wise manner. In contrast, BFS utilizes a queue to visit nodes level by level. The example highlights algorithms' behavior using a graph of Australian cities, including Sydney, Canberra, and Melbourne, and how they influence the search order and outcomes.

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Comparing Depth-First and Breadth-First Search Algorithms in Graph Traversal

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  1. START END

  2. Depth-First Search Stack Contents: V0 V4, V1 V4, V3 V4, V6, V5 V4, V6 V4 Empty V0 V2 V1 V4 V6 V3 V5 A traversal processes only those vertices that can be reached from the start vertex.

  3. Breadth-First Search Queue Contents: V0 V1, V4 V4, V3 V3 V6, V5 V5 Empty V0 V2 V1 V4 V6 V3 V5

  4. Darwin • DFS: • Sydney • Canberra • Brisbane • Adelaide • Melbourne • Hobart • Perth • Black Stump • Darwin • BFS: • Sydney • Canberra • Melbourne • Brisbane • Adelaide • Hobart • Perth • Black Stump • Darwin Black Stump Brisbane Adelaide Perth Canberra Sydney Melbourne Hobart

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