Leaves - Samantha

[iamsammysam]

Heaps Practice

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Comprehension Questions

Question	Answer
How is a Heap different from a Binary Search Tree?	Heap is an almost complete tree, where every level of the tree if full except from the last level, that must be filled left to right.
Could you build a heap with linked nodes?	Yes, but it is way easier to implement it with an array.
Why is adding a node to a heap an O(log n) operation?	Performing the heap-up operation will at worst-case perform one swap per level of the heap and there are log n levels to the heap.
Where the heap_up & heap_down methods useful? Why?	Heap_up => to add an element to the heap. You place it into the end of the array, then you do a "heap-up" operation comparing the new node to its parent and swapping them if they are out of order. Heap_down => to remove an element from the heap. You swap the last leaf with the root, then compare the new root with its children and swap to maintain the heap order using. the operation heap-down. The heap down operation is repeated until a leaf node is reached or no swaps are made.

[CheezItMan]

I apologize for taking so long to look at this. You did a fantastic job here. The code is clean and readable and everything works well. A few small things on space complexity, otherwise great!

[CheezItMan]

You are building a heap here... so you DO have some space complexity even if that heap is empty by the end.

[CheezItMan]

👍

[CheezItMan]

👍

[CheezItMan]

👍

[CheezItMan]

You do have space complexity here brought upon by the recursion involved.

[CheezItMan]

Very clean code here I like it!

[iamsammysam]

Thank you Chris! I appreciate the feedback.

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On Fri, Apr 17, 2020 at 1:06 PM Chris M ***@***.***> wrote: ***@***.**** commented on this pull request. I apologize for taking so long to look at this. You did a fantastic job here. The code is clean and readable and everything works well. A few small things on space complexity, otherwise great! ------------------------------ In lib/heap_sort.rb <#33 (comment)>: > +# Time Complexity: On(log n) +# Space Complexity: O(1) def heap_sort(list) You are building a heap here... so you DO have some space complexity even if that heap is empty by the end. ------------------------------ In lib/min_heap.rb <#33 (comment)>: > + # Time Complexity: O(log n) + # Space Complexity: O(log n) def add(key, value = key) 👍 ------------------------------ In lib/min_heap.rb <#33 (comment)>: > + # Time Complexity: O(log n) + # Space Complexity: O(log n) def remove() 👍 ------------------------------ In lib/min_heap.rb <#33 (comment)>: > + # Time complexity: O(1) + # Space complexity: O(1) def empty? 👍 ------------------------------ In lib/min_heap.rb <#33 (comment)>: > + # Time complexity: O(log n) + # Space complexity: O(1) def heap_up(index) You do have space complexity here brought upon by the recursion involved. ------------------------------ In lib/min_heap.rb <#33 (comment)>: > 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) Very clean code here I like it! — You are receiving this because you authored the thread. Reply to this email directly, view it on GitHub <#33 (review)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AMMQ6O7QG5HAUDTBINFZVTLRNCZFZANCNFSM4L6YAJKQ> .