If you have a pointer to the node to be deleted, the deletion can be done in constant time, O(1).

If you have a pointer to the node to be deleted, the deletion can be done in constant time, O(1).

The time complexity is O(n) in the worst case, as you may need to traverse the list to find the element to delete.

Deleting an element from the front of a queue implemented with a linked list is done in constant time, O(1).

Deleting from the front of a linked list queue is a constant time operation, hence O(1).

Deleting an element from the front of a queue is done in constant time, hence O(1).

If you have a pointer to the node to be deleted, the deletion can be done in O(1) time.

Deleting an element from a stack (pop operation) is done in constant time, hence O(1).

Deleting the last element from a dynamic array is a constant time operation, so the time complexity is O(1).

To delete the last element from a singly linked list, you must traverse the list to find the second-to-last element, resulting in O(n) time complexity.

To delete the last node in a singly linked list, you must traverse the list to find the second-to-last node, resulting in O(n) time complexity.

DFS visits each vertex and edge once, leading to a time complexity of O(V + E), where V is vertices and E is edges.

DFS explores all vertices (V) and edges (E) in the graph, leading to a time complexity of O(V + E).

Dequeuing an element from a queue implemented using a circular array can be done in constant time, O(1), as it involves adjusting the front index.

Dequeuing from a queue implemented with a linked list is O(1) as it involves removing the head node.

Dequeuing an element from a queue implemented using an array can take O(n) time if all elements need to be shifted after removing the front element.

The time complexity of Dijkstra's algorithm using a binary heap is O(E log V), where E is the number of edges and V is the number of vertices.

Dijkstra's algorithm has a time complexity of O(E log V) when using a priority queue implemented with a binary heap, where E is the number of edges and V is the number of vertices.

Dijkstra's algorithm has a time complexity of O(E log V) when implemented with a priority queue.

When using a binary heap, the time complexity of Dijkstra's algorithm is O(E log V), where E is the number of edges and V is the number of vertices.

When implemented with a binary heap, the time complexity of Dijkstra's algorithm is O(E log V), where E is the number of edges and V is the number of vertices.

The time complexity of Dijkstra's algorithm using a binary heap is O(E log V), where E is the number of edges and V is the number of vertices.

Both enqueue and dequeue operations can be performed in constant time O(1) in a linked list implementation.

Both enqueue and dequeue operations can be performed in constant time, O(1), when using a linked list.

Both enqueue and dequeue operations in a queue implemented using a linked list have a time complexity of O(1).

Enqueueing an element in a queue implemented using an array can be done in constant time, O(1), if there is space available.

Enqueueing an element in a queue implemented with a linked list is done in constant time, O(1), as it involves adding to the tail of the list.

Enqueueing an element in a queue implemented with a linked list is done in constant time, O(1), by adding the element to the end of the list.

Enqueueing an element in a queue is done in constant time, hence O(1).

Enqueuing an element in a queue implemented using an array is done in constant time, O(1), unless the array needs to be resized.