Heap extraction (bubble down) in Data Structures Theory - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to identify the root element in a max-heap.

Data Structures Theory

root = heap[[1]]

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A0

B1

C-1

Dlen(heap)

Attempts:

3 left

💡 Hint

Common Mistakes

Using 1 as the root index, which is incorrect for zero-based arrays.

Using -1 or len(heap) which are invalid indices for the root.

The root element of a max-heap is always at index 0 in the array representation.

2fill in blank

medium

Complete the code to find the left child index of a node at index i in a heap.

Data Structures Theory

left_child = 2 * i [1] 1

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A-

B+

C*

D//

Attempts:

3 left

💡 Hint

Common Mistakes

Using subtraction instead of addition.

Using division or multiplication incorrectly.

In a heap, the left child of node at index i is at 2*i + 1.

3fill in blank

hard

Fix the error in the condition to check if the right child exists in the heap array.

Data Structures Theory

if right_child_index [1] len(heap):

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A<

B<=

C>

D>=

Attempts:

3 left

💡 Hint

Common Mistakes

Using <= which allows out-of-range index.

Using > or >= which are incorrect for existence check.

The right child exists only if its index is less than the length of the heap array.

4fill in blank

hard

Fill both blanks to correctly swap the parent with the larger child during bubble down.

Data Structures Theory

if heap[[1]] < heap[[2]]:
    heap[[1]], heap[[2]] = heap[[2]], heap[[1]]

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Aparent_index

Bleft_child_index

Cright_child_index

Droot_index

Attempts:

3 left

💡 Hint

Common Mistakes

Swapping with the left child when the right child is larger.

Using root_index instead of parent_index.

During bubble down, the parent is swapped with the larger child, here the right child index is used.

5fill in blank

hard

Fill all three blanks to complete the bubble down step choosing the larger child correctly.

Data Structures Theory

larger_child = [1] if heap[[2]] > heap[[3]] else [3]

Drag options to blanks, or click blank then click option'

Aleft_child_index

Bright_child_index

Attempts:

3 left

💡 Hint

Common Mistakes

Mixing up left and right child indices in the comparison.

Using the same index for both comparison sides.

This line selects the larger child index by comparing left and right child values.