Heap Insert Operation Bubble Up in DSA Typescript - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is the purpose of the bubble up operation in a heap insert?

The bubble up operation moves the newly inserted element up the heap to restore the heap property, ensuring the parent node is smaller (min-heap) or larger (max-heap) than its children.

beginner

In a min-heap, when does the bubble up operation stop?

It stops when the inserted element is greater than or equal to its parent or when it reaches the root of the heap.

intermediate

What is the time complexity of the bubble up operation in a heap?

The time complexity is O(log n), where n is the number of elements in the heap, because the element moves up at most the height of the heap.

beginner

Which index calculation is used to find the parent of a node at index i in a heap array?

The parent index is calculated as Math.floor((i - 1) / 2).

beginner

Explain the bubble up process with an example of inserting 5 into a min-heap [2, 4, 7].

Insert 5 at the end: [2, 4, 7, 5]. Compare 5 with parent 4. Since 5 > 4, no swap needed. Bubble up stops. Final heap: [2, 4, 7, 5].

What does the bubble up operation do after inserting a new element in a min-heap?

A Removes the smallest element

B Moves the element up until it is larger than its parent

C Moves the element down to maintain heap property

D Moves the element up until it is no longer smaller than its parent

In a min-heap, bubble up moves the new element up until it is no longer smaller than its parent.

What is the parent index of the node at index 6 in a heap array?

A 1

B 3

C 2

D 4

Parent index = Math.floor((6 - 1) / 2) = Math.floor(5 / 2) = 2.

When inserting into a max-heap, bubble up continues as long as the inserted element is:

A Larger than its parent

B Smaller than its parent

C Equal to its parent

D At the root

In a max-heap, bubble up moves the element up while it is larger than its parent.

What is the worst-case time complexity of bubble up in a heap with n elements?

A O(log n)

B O(n)

C O(1)

D O(n log n)

Bubble up moves up the height of the heap, which is log n.

If the newly inserted element is at the root after bubble up, what does it mean?

A Heap property is violated

B The element is the smallest or largest

C The heap is empty

D Heap property is restored

If bubble up reaches root, the element is the smallest (min-heap) or largest (max-heap).

Describe the bubble up operation during heap insertion and why it is necessary.

Think about how the heap keeps order after adding a new value.

Explain how to find the parent index of a node in a heap stored as an array and how it is used in bubble up.

Remember the formula involves dividing the current index.

Practice

1. What is the main purpose of the bubble up operation during a heap insert?

easy

A. To swap all elements randomly in the heap

B. To remove the root element from the heap

C. To sort all elements in the heap in ascending order

D. To restore the heap property by moving the new element up if it is smaller (min-heap) or larger (max-heap) than its parent

Solution

1. Step 1: Understand the heap property

   In a min-heap, each parent node must be smaller than its children. In a max-heap, each parent must be larger.

2. Step 2: Purpose of bubble up

   When inserting a new element, it is placed at the end. Bubble up moves it up the tree to restore the heap property if violated.

3. Final Answer:

   To restore the heap property by moving the new element up if it is smaller (min-heap) or larger (max-heap) than its parent -> Option D

4. Quick Check:

   Bubble up fixes heap order after insert [OK]

Hint: Bubble up fixes heap order by moving new element up [OK]

Common Mistakes:

• Confusing bubble up with removing elements
• Thinking bubble up sorts the entire heap
• Assuming bubble up swaps elements randomly

2. Which of the following TypeScript code snippets correctly performs the bubble up step in a min-heap after inserting a new element at the end?

easy

A. while (index > 0 && heap[index] < heap[parentIndex]) { swap(heap, index, parentIndex); index = parentIndex; }

B. while (index > 0 && heap[index] > heap[parentIndex]) { swap(heap, index, parentIndex); index = parentIndex; }

C. for (let i = 0; i < heap.length; i++) { if (heap[i] < heap[i+1]) swap(heap, i, i+1); }

D. if (heap[index] > heap[parentIndex]) { swap(heap, index, parentIndex); }

Solution

1. Step 1: Identify min-heap bubble up condition

   In a min-heap, bubble up swaps while the child is smaller than the parent.

2. Step 2: Check code correctness

   while (index > 0 && heap[index] < heap[parentIndex]) { swap(heap, index, parentIndex); index = parentIndex; } uses a while loop with condition heap[index] < heap[parentIndex], correctly swapping and updating index.

3. Final Answer:

   while (index > 0 && heap[index] < heap[parentIndex]) { swap(heap, index, parentIndex); index = parentIndex; } -> Option A

4. Quick Check:

   Min-heap bubble up swaps smaller child up [OK]

Hint: Bubble up swaps while child < parent in min-heap [OK]

Common Mistakes:

• Using > instead of < for min-heap
• Using for loop instead of while
• Not updating index after swap

3. Given a max-heap represented as an array: [50, 30, 40, 10, 20], what will be the heap array after inserting 45 and performing bubble up?

medium

A. [50, 45, 40, 10, 20, 30]

B. [50, 30, 45, 10, 20, 40]

C. [50, 30, 40, 10, 20, 45]

D. [45, 30, 50, 10, 20, 40]

Solution

1. Step 1: Insert 45 at the end

   Array becomes [50, 30, 40, 10, 20, 45]

2. Step 2: Bubble up 45 in max-heap

   Parent index of 45 (index 5) is 2 (value 40). Since 45 > 40, swap. New array: [50, 30, 45, 10, 20, 40]. Now index 2's parent is 0 (value 50). 45 < 50, stop bubbling up.

3. Final Answer:

   [50, 30, 45, 10, 20, 40] -> Option B

4. Quick Check:

   Bubble up swaps 45 with 40 only [OK]

Hint: Insert at end, swap up while child > parent in max-heap [OK]

Common Mistakes:

• Not swapping 45 with 40
• Swapping 45 with 30 instead of 40
• Stopping bubble up too early

4. Consider this bubble up code snippet for a min-heap insert:

while (index > 0 && heap[index] > heap[parentIndex]) {
  swap(heap, index, parentIndex);
  index = parentIndex;
}

What is the error in this code?

medium

A. The parentIndex is not updated inside the loop

B. The swap function is called incorrectly

C. The comparison operator should be '<' to maintain min-heap property

D. The loop should run while index < 0

Solution

1. Step 1: Check comparison for min-heap bubble up

   In a min-heap, bubble up swaps when child is smaller than parent, so condition should be heap[index] < heap[parentIndex].

2. Step 2: Identify error in code

   The code uses '>' which is incorrect for min-heap bubble up, causing wrong swaps.

3. Final Answer:

   The comparison operator should be '<' to maintain min-heap property -> Option C

4. Quick Check:

   Min-heap bubble up uses < comparison [OK]

Hint: Min-heap bubble up swaps when child < parent [OK]

Common Mistakes:

• Using > instead of < in condition
• Not updating parentIndex after swap
• Loop condition index > 0 is correct, not < 0

5. You have a min-heap represented as [5, 10, 15, 20, 25, 30]. You insert 12 and perform bubble up. After that, you insert 3 and perform bubble up again. What is the final heap array?

hard

A. [3, 5, 12, 10, 25, 30, 15, 20]

B. [3, 5, 15, 10, 25, 30, 12, 20]

C. [3, 5, 12, 20, 25, 30, 15, 10]

D. [3, 5, 15, 20, 25, 30, 12, 10]

Solution

1. Step 1: Insert 12 and bubble up

   Insert 12 at index 6: [5,10,15,20,25,30,12]. Parent of index 6 is 2 (value 15). Since 12 < 15, swap: [5,10,12,20,25,30,15]. Parent of index 2 is 0 (value 5). 12 > 5, stop.

2. Step 2: Insert 3 and bubble up

   Insert 3 at index 7: [5,10,12,20,25,30,15,3]. Parent of index 7 is 3 (value 20). 3 < 20, swap: [5,10,12,3,25,30,15,20]. Parent of index 3 is 1 (value 10). 3 < 10, swap: [5,3,12,10,25,30,15,20]. Parent of index 1 is 0 (value 5). 3 < 5, swap: [3,5,12,10,25,30,15,20]. Now at root, stop.

3. Final Answer:

   [3, 5, 12, 10, 25, 30, 15, 20] -> Option A

4. Quick Check:

   Bubble up swaps until heap property restored [OK]

Hint: Bubble up each insert until parent smaller in min-heap [OK]

Common Mistakes:

• Not swapping 3 all the way to root
• Incorrect parent index calculation
• Stopping bubble up too early