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Leaves - Alice #19

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Heaps Practice

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Comprehension Questions

Question Answer
How is a Heap different from a Binary Search Tree? A heap guarantees that the elements on the higher level are greater (max heap) or lower (min heap). A BST guarantees order from left to right.
Could you build a heap with linked nodes? Yes.
Why is adding a node to a heap an O(log n) operation? There are log n levels to the heap, so adding a node to it is also log n.
Were the heap_up & heap_down methods useful? Why? Yes, because it was able to bubble up/down the nodes to the appropriate place.

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@CheezItMan CheezItMan left a comment

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Nice work, you hit the majority of the learning goals here. Well done. Do see my notes on time/space complexities. Something to pay more attention to in the future. Let me know if you have questions.

Comment on lines 4 to +6
# Time Complexity: ?
# Space Complexity: ?
def heap_sort(list)
raise NotImplementedError, "Method not implemented yet..."
def heapsort(list)

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No time and space complexity estimates?

Comment on lines +17 to 19
# Time Complexity: O(log n)
# Space Complexity: O(1)
def add(key, value = key)

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👍

Comment on lines +27 to 29
# Time Complexity: O(log n)
# Space Complexity: O(n)
def remove()

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👍

Comment on lines +55 to 57
# Time complexity: O(1)
# Space complexity: O(1)
def empty?

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👍

Comment on lines +66 to 68
# Time complexity: O(1)
# Space complexity: O(1)
def heap_up(index)

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O(1) for Both time and space? One thing to consider is that you're doing recursion, so that will also incur space complexity and you'll have to heap_up log n times (max).

end


# This helper method takes an index and
# moves it up the heap if it's smaller
# than it's parent node.
def heap_down(index)

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👍

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2 participants