So you just push them out one by one and you have a sorted queue. Mark the current node as True in the visited array. A topological sort is a graph traversal in which each node v is only visited after all of its dependencies have been visited. Run a loop from 0 till N if the node is not marked True in visited array Call the recursive function for topological sort and perform the following steps. The stack now contains all the numbers with the top being the smallest number. Heres my introduction to stacks, queues, and deques (double-ended queues)You can check out the problem I mentioned at the end of the video here: https://ww. Initialize visited array of size N to keep the record of visited nodes. Repeat this process until the queue is empty. Lets see how we can find a topological sorting in a graph. You can just rotate the queue by actions: "xo" (move the first number to the end of the queue) and when you reach the largest number, push it to the stack. So topological sorting can be achieved for only directed and acyclic graphs. Constraints Stacks, unfortunately, don’t offer constant-time access to the nth item in the stack, unlike an array. This is due to the fact that we don’t need to shift items around to add and remove them from the stack. In the above example, the following actions sort the queue in ascending order:Īny idea how can I solve this problem with the minimum number of actions?Īctually, it should be with a minimum number of steps, as there is a dummy solution: Benefits Stacks allow for constant-time adding and removing of an item. Action "o": Pop an element from the stack and enqueue it in the queue.Action 'o': Pop an element from the stack and enqueue it in the queue. Action "x": Dequeue an element from the queue and push it to the stack. Action 'x': Dequeue an element from the queue and push it to the stack.Suppose we have N natural numbers in a queue.
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