Table of Contents
What is the time and space complexity of BFS?
O(|V|) = O(b^d)Breadth-first search / Space complexity
What is the time complexity of breadth-first search algorithm?
The Time complexity of BFS is O(V + E) when Adjacency List is used and O(V^2) when Adjacency Matrix is used, where V stands for vertices and E stands for edges.
What is time complexity of breadth-first search algorithm Mcq?
Explanation: The Breadth First Search explores every node once and every edge once (in worst case), so it’s time complexity is O(V + E). 3.
Which has more space complexity BFS or DFS?
The time complexity of both algorithms is the same. But in the case of space complexity, if the maximum height is less than the maximum number of nodes in a single level, then DFS will be more space optimised than BFS or vice versa.
What is the space complexity of Depth First Search?
The space complexity for DFS is O(h) where h is the maximum height of the tree.
Which takes less space BFS or DFS?
The DFS needs less memory as it only has to keep track of the nodes in a chain from the top to the bottom, while the BFS has to keep track of all the nodes on the same level. For example, in a (balanced) tree with 1023 nodes the DFS has to keep track of 10 nodes, while the BFS has to keep track of 512 nodes.
What is time complexity of breadth first search algorithm Mcq?
What is more important time complexity and space complexity?
Time complexity is often actually less important than space complexity, though obviously both matter. Sometimes time complexity matters more however. Your space is fixed for any set of hardware. If you don’t have enough, you just can’t run the algorithm.
What is the time complexity of breadth first search algorithm Mcq?
Which takes more space BFS or DFS?
BFS uses a larger amount of memory because it expands all children of a vertex and keeps them in memory. It stores the pointers to a level’s child nodes while searching each level to remember where it should go when it reaches a leaf node.