Heap Sort Algorithm in DSA Go - Interactive Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to swap two elements in the slice.

DSA Go

func swap(arr []int, i, j int) {
    temp := arr[[1]]
    arr[i] = arr[j]
    arr[j] = temp
}

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

Ai

Bj

C0

Dlen(arr)-1

Attempts:

3 left

💡 Hint

Common Mistakes

Using the wrong index like j or 0 for temp storage.

Forgetting to store the value before overwriting.

The swap function uses the index i to temporarily store the value before swapping.

2fill in blank

medium

Complete the code to find the left child index in the heap.

DSA Go

func leftChild(i int) int {
    return 2*[1] + 1
}

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

A1

B2

Ci

D0

Attempts:

3 left

💡 Hint

Common Mistakes

Using a fixed number instead of the variable i.

Adding 2 instead of 1.

The left child index in a heap is calculated as 2*i + 1.

3fill in blank

hard

Fix the error in the heapify function to correctly compare parent and child nodes.

DSA Go

func heapify(arr []int, n, i int) {
    largest := i
    l := 2*i + 1
    r := 2*i + 2

    if l < n && arr[l] [1] arr[largest] {
        largest = l
    }

    if r < n && arr[r] > arr[largest] {
        largest = r
    }

    if largest != i {
        swap(arr, i, largest)
        heapify(arr, n, largest)
    }
}

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

A!=

B==

C<

D>

Attempts:

3 left

💡 Hint

Common Mistakes

Using '<' which breaks max-heap property.

Using '==' or '!=' which are incorrect for comparison.

To maintain max-heap property, we check if child is greater than parent.

4fill in blank

hard

Fill both blanks to build the max heap from the array.

DSA Go

func buildMaxHeap(arr []int, n int) {
    for i := n/[1] - 1; i >= 0; i-- {
        heapify(arr, n, [2])
    }
}

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

A2

Bi

C1

Dn

Attempts:

3 left

💡 Hint

Common Mistakes

Using n or 1 instead of 2 for division.

Passing wrong index to heapify.

We start heapify from the last parent node at n/2 -1 down to 0.

5fill in blank

hard

Fill all three blanks to complete the heap sort main loop.

DSA Go

func heapSort(arr []int) {
    n := len(arr)
    buildMaxHeap(arr, n)

    for i := n - 1; i > 0; i-- {
        swap(arr, 0, [1])
        heapify(arr, [2], [3])
    }
}

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

Ai

C0

Dn - 1

Attempts:

3 left

💡 Hint

Common Mistakes

Using wrong indices for swap or heapify.

Not reducing heap size correctly.

Swap root with last element i, then heapify with reduced size i and root index 0.

Practice

1. What is the main purpose of the heap in the Heap Sort algorithm?

easy

A. To efficiently find and remove the largest (or smallest) element

B. To store elements in sorted order permanently

C. To reverse the order of elements in the array

D. To count the number of elements in the array

Solution

1. Step 1: Understand heap property

   A heap is a special tree-based structure where the parent node is either greater (max-heap) or smaller (min-heap) than its children, allowing quick access to the largest or smallest element.

2. Step 2: Role in Heap Sort

   Heap Sort uses this property to repeatedly extract the largest element from the heap and place it at the end of the array, sorting the array efficiently.

3. Final Answer:

   To efficiently find and remove the largest (or smallest) element -> Option A

4. Quick Check:

   Heap = fast max/min extraction [OK]

Hint: Heap helps quickly get max/min element for sorting [OK]

Common Mistakes:

• Thinking heap stores sorted elements permanently
• Confusing heap with a simple array
• Believing heap reverses array order

2. Which of the following is the correct way to swap two elements in Go during Heap Sort?

easy

A. arr[i] = arr[j]; arr[j] = arr[i]

B. arr[i], arr[j] = arr[j], arr[i]

C. swap(arr[i], arr[j])

D. temp = arr[i]; arr[j] = arr[i]; arr[i] = temp

Solution

1. Step 1: Understand Go multiple assignment

   Go allows swapping two variables in one line using multiple assignment syntax: arr[i], arr[j] = arr[j], arr[i].

2. Step 2: Check other options

   swap(arr[i], arr[j]) is invalid syntax in Go. arr[i] = arr[j]; arr[j] = arr[i] overwrites arr[i] before assigning arr[j]. temp = arr[i]; arr[j] = arr[i]; arr[i] = temp incorrectly sets arr[j] to old arr[i] and leaves arr[i] unchanged.

3. Final Answer:

   arr[i], arr[j] = arr[j], arr[i] -> Option B

4. Quick Check:

   Go swap uses multiple assignment [OK]

Hint: Use Go's multiple assignment to swap variables [OK]

Common Mistakes:

• Using invalid swap function call
• Overwriting one element before swapping
• Using incorrect temp assignment sequence

3. What will be the output array after applying Heap Sort on [4, 10, 3, 5, 1]?

medium

A. [1, 3, 4, 5, 10]

B. [10, 5, 4, 3, 1]

C. [1, 4, 3, 5, 10]

D. [5, 10, 4, 3, 1]

Solution

1. Step 1: Build max heap from array

   Heapify the array to get max heap: [10, 5, 3, 4, 1]

2. Step 2: Extract max and sort

   Repeatedly swap max with last element and heapify remaining: final sorted array is [1, 3, 4, 5, 10]

3. Final Answer:

   [1, 3, 4, 5, 10] -> Option A

4. Quick Check:

   Heap Sort sorts ascending [OK]

Hint: Heap Sort outputs sorted array in ascending order [OK]

Common Mistakes:

• Confusing max heap with sorted array
• Forgetting to heapify after swaps
• Assuming heap sort outputs descending order

4. Identify the bug in this Go heapify function snippet used in Heap Sort:

func heapify(arr []int, n, i int) {
  largest := i
  l := 2*i + 1
  r := 2*i + 2
  if l < n && arr[l] > arr[largest] {
    largest = l
  }
  if r < n && arr[r] > arr[largest] {
    largest = r
  }
  if largest != i {
    arr[i], arr[largest] = arr[largest], arr[i]
    heapify(arr, n, i)
  }
}

medium

A. Swap syntax is invalid in Go

B. Indices l and r are calculated incorrectly

C. Recursive call should be heapify(arr, n, largest) instead of heapify(arr, n, i)

D. Function should return a value

Solution

1. Step 1: Analyze recursive call

   After swapping, heapify must continue from the new largest index to fix subtree, so call should be heapify(arr, n, largest).

2. Step 2: Check other parts

   Indices l and r are correct for binary heap. Swap syntax is valid Go. Function does not need to return value.

3. Final Answer:

   Recursive call should be heapify(arr, n, largest) instead of heapify(arr, n, i) -> Option C

4. Quick Check:

   Recursive call uses largest index [OK]

Hint: After swap, heapify from largest child index [OK]

Common Mistakes:

• Recursing on wrong index after swap
• Miscomputing child indices
• Thinking swap syntax is wrong in Go

5. Given an array with many duplicate values, how does Heap Sort behave compared to Quick Sort in terms of stability and performance?

hard

A. Both Heap Sort and Quick Sort are stable and have same worst-case time

B. Heap Sort is stable and faster than Quick Sort always

C. Quick Sort is stable and always faster than Heap Sort

D. Heap Sort is not stable but has consistent O(n log n) time; Quick Sort is unstable and may degrade to O(n²)

Solution

1. Step 1: Understand stability and time complexity

   Heap Sort is not stable because it swaps elements that may change relative order. It guarantees O(n log n) time always.

2. Step 2: Compare with Quick Sort

   Quick Sort is also not stable and can degrade to O(n²) in worst case, but often faster on average.

3. Final Answer:

   Heap Sort is not stable but has consistent O(n log n) time; Quick Sort is unstable and may degrade to O(n²) -> Option D

4. Quick Check:

   Heap Sort stable? No; Quick Sort worst-case O(n²) [OK]

Hint: Heap Sort always O(n log n), unstable; Quick Sort can be slower [OK]

Common Mistakes:

• Assuming Heap Sort is stable
• Thinking Quick Sort is always faster
• Confusing stability with sorting speed