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CheezItMan
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May 6, 2021
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Nice work Sophie, this hits the learning goals here. Well done.
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| # Time Complexity: n log(n) | ||
| # Space Complexity: n | ||
| def heap_sort(list) |
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| # Time Complexity: log n | ||
| # Space Complexity: log n | ||
| def add(key, value = key) |
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| # Time Complexity: log n | ||
| # Space Complexity: log n | ||
| def remove() |
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| # Time complexity: 1 | ||
| # Space complexity: 1 | ||
| def empty? |
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👍
Suggested change
| # Time complexity: 1 | |
| # Space complexity: 1 | |
| def empty? | |
| # Time complexity: O(1) | |
| # Space complexity: O(1) | |
| def empty? |
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| # Time complexity: log n | ||
| # Space complexity: log n | ||
| def heap_up(index) |
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| if @store[left].key < @store[index].key | ||
| # recursive case - left node | ||
| swap(left, index) | ||
| heap_down(left) | ||
| end | ||
| if right < @store.length && @store[right].key < @store[index].key | ||
| # recursive case - right node | ||
| swap(right, index) | ||
| heap_down(right) | ||
| end |
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This works, but you might engage in extra swaps if the sequential if statements.
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| # Time complexity: log n | ||
| # Space complexity: log n | ||
| def heap_down(index) |
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Heaps Practice
Congratulations! You're submitting your assignment!
Comprehension Questions
heap_up&heap_downmethods useful? Why?