The worst-case time complexity for inserting an element into a Red-Black tree is O(log n) due to its balanced structure.

The worst-case time complexity for insertion in a Red-Black tree is O(log n).

The worst-case time complexity for insertion in an AVL tree is O(log n) because the tree remains balanced.

The worst-case time complexity for searching an element in a balanced binary search tree is O(log n).

In the worst case, a BST can degenerate into a linked list, leading to a time complexity of O(V).

In the worst case, a binary search tree can degenerate into a linked list, leading to a search time complexity of O(n).

In the worst case, you may have to traverse the entire linked list to find an element, resulting in O(n) time complexity.

In a queue, searching for an element requires traversing the entire queue, leading to a worst-case time complexity of O(n).

The worst-case time complexity for searching an element in a Red-Black Tree is O(log n) due to its balanced nature.

Binary search has a worst-case time complexity of O(log n) for searching in a sorted array.

In the worst case, you may need to check every element in the array, leading to O(n) time complexity.

In the worst case, you may have to traverse the entire linked list, leading to O(n) time complexity.

The worst-case time complexity for searching an element in an unsorted stack is O(n), as you may need to check each element.

The worst-case time complexity for searching in a Red-Black tree is O(log n) due to its balanced nature.

In the worst case, binary search still operates in O(log n) time complexity.

The worst-case time complexity of bubble sort is O(n^2) when the array is sorted in reverse order.

The worst-case time complexity of DFS is O(V + E) for an adjacency list representation.

In the worst case, DFS will check all entries in the adjacency matrix, leading to a time complexity of O(V^2).

The worst-case time complexity of DFS is O(V + E) as it visits each vertex and edge once.

The worst-case time complexity of DFS is O(V + E), as it visits every vertex and edge in the graph.

The worst-case time complexity of DFS is O(V + E), as it visits each vertex and edge once.

When using an adjacency matrix, the worst-case time complexity of Dijkstra's algorithm is O(V^2) because each vertex must be checked against all others.

The worst-case time complexity of Heap Sort is O(n log n) because it builds a heap and then sorts it.

Inserting at the beginning of a singly linked list is a constant time operation, O(1).

Inserting at the end of a singly linked list requires traversing the entire list, resulting in O(n) time complexity.

The worst-case time complexity of inserting an element in a binary search tree is O(n), which occurs when the tree becomes unbalanced.

The worst-case time complexity of inserting an element into a binary search tree is O(n), which occurs when the tree becomes unbalanced.

Inserting an element in a linked list requires traversing the list in the worst case, leading to O(n).

Inserting an element in a linked list can take O(n) time in the worst case if the position is at the end and traversal is required.

In the worst case, you may need to traverse the entire list to find the insertion point, resulting in O(n) time complexity.