Difference Between BFS and DFS
Introduction
The main difference between BFS and DFS is that BFS goes level by level, but DFS takes a route from the beginning to the end node (vertex), then another path from the end to the beginning, and so on until all nodes are visited. In addition, BFS utilizes the queue to store nodes, while DFS uses the stack to traverse nodes.
The traversal techniques for searching a graph are BFS and DFS. The process of visiting all nodes in a graph is known as graph traversal. A graph is made up of vertices (V) and edges (E) that link them.
What is BFS?
Breadth First Search (also known as BFS) is a search strategy for broadening all nodes in a graph. It does this job by examining and expanding these nodes by seeking every single solution (or a combination of sequences therein). A BFS does not utilize a heuristic algorithm as a result (or an algorithm that searches for a solution through multiple scenarios). After all of the nodes have been acquired, they are placed in the First In, First Out queue. Nodes that have not been investigated are'stored' in a 'open' container, and once explored, they are moved to a 'closed' container.
What is DFS?
Depth First Search (DFS) is a search strategy that digs deeper into a child node of a search until it reaches a target (or until it reaches a node with no additional permutations or 'children'). After locating one target, the search returns to a previous node that yielded a solution, and so on until all nodes have been successfully searched. As a result, nodes are kept aside for future investigation — this is known as non-recursive implementation.
Comparison Between BFS and DFS
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DFS |
- BFS stands for Breadth-First Search in its complete form.
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- Depth First Search is the full version of DFS.
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- BFS is used to identify the shortest distance between two nodes, and it begins at the first or root node and goes across all of the nodes related to it. After looking at the example below, you'll have a better understanding of how it works.
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- DFS is a depth-first strategy, completing the entire route via all nodes connected to the node in question. After looking at the example below, you'll have a better understanding of how it works.
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- It is carried out according to the First In First Out philosophy (FIFO).
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- The Stack concept, or the Last In First Out method, is used (LIFO).
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- Nodes that have been traversed several times are removed from the queue.
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- The visited nodes are added onto the stack, and they are subsequently deleted if there are no more nodes to be visited.
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- It is more time consuming than Depth First Search
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- It outperforms the Breadth-First Search algorithm in terms of speed.
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- The Depth First Search technique isn't the only way to allocate memory.
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- Memory use is lower than that of the Breadth-First Search Algorithm.
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Conclusion
The aforementioned algorithms are used as machine learning or to identify artificial intelligence-related solutions in a variety of applications. They're mostly utilized in graphs to determine if they're bipartite or not, as well as to discover related component cycles. They are also significant algorithms for determining the shortest distance or locating the route. We may employ two algorithms, depending on the needs of the company. However, the Breadth-First Search method is preferred over the Depth First Search technique.
