Quick Sort as Divide and Conquer in DSA C++ - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is the main idea behind Quick Sort as a divide and conquer algorithm?

Quick Sort divides the array into smaller parts around a pivot, sorts each part independently, and then combines them to get the sorted array.

beginner

What role does the pivot play in Quick Sort?

The pivot is the element used to split the array into two parts: elements less than the pivot go to the left, and elements greater go to the right.

intermediate

Explain the partition step in Quick Sort.

Partition rearranges the array so that all elements less than the pivot come before it, and all greater elements come after it, placing the pivot in its correct sorted position.

intermediate

Why is Quick Sort considered efficient on average?

Because it divides the problem into smaller parts and sorts them quickly, usually in O(n log n) time, making it faster than simple sorting methods for large data.

advanced

What is the worst-case time complexity of Quick Sort and when does it happen?

The worst-case time is O(n²), which happens when the pivot divides the array very unevenly, like always picking the smallest or largest element as pivot.

What does Quick Sort use to divide the array?

A A pivot element

B A temporary array

C A stack

D A queue

Quick Sort uses a pivot element to split the array into parts.

After partitioning, where is the pivot placed?

A At the start of the array

B In the middle of the array regardless of order

C At the end of the array

D At its correct sorted position

The pivot is placed at its correct sorted position after partitioning.

What is the average time complexity of Quick Sort?

A O(log n)

B O(n²)

C O(n log n)

D O(n)

Quick Sort usually runs in O(n log n) time on average.

Which of these is NOT a step in Quick Sort?

A Divide the array using a pivot

B Merge the sorted parts

C Sort the divided parts recursively

D Partition the array

Quick Sort does not merge parts; it sorts in place after partitioning.

What causes Quick Sort to have its worst-case performance?

A Choosing the smallest or largest element as pivot repeatedly

B Choosing a random pivot

C Choosing the middle element as pivot

D Using extra memory

Picking the smallest or largest element as pivot repeatedly causes unbalanced splits and worst-case O(n²) time.

Describe how Quick Sort uses divide and conquer to sort an array.

Think about how the array is split and sorted step by step.

Explain why the choice of pivot affects Quick Sort's performance.

Consider what happens if the pivot is always the smallest or largest element.

Practice

1. What is the main idea behind the Quick Sort algorithm as a divide and conquer method?

easy

A. Use extra memory to merge two sorted arrays

B. Sort the array by repeatedly swapping adjacent elements

C. Divide the array into smaller parts, sort them, and combine results

D. Sort the array by selecting the smallest element each time

Solution

1. Step 1: Understand divide and conquer in Quick Sort

   Quick Sort divides the array into parts around a pivot, then sorts each part separately.

2. Step 2: Recognize the sorting and combining process

   After dividing, it sorts the parts recursively and combines them by the nature of recursion.

3. Final Answer:

   Divide the array into smaller parts, sort them, and combine results -> Option C

4. Quick Check:

   Divide and conquer = divide, sort, combine [OK]

Hint: Remember: divide, sort parts, then combine [OK]

Common Mistakes:

• Confusing Quick Sort with Bubble Sort
• Thinking Quick Sort uses extra memory like Merge Sort
• Believing Quick Sort selects smallest element each time

2. Which of the following is the correct way to declare the partition function header in C++ for Quick Sort?

easy

A. void partition(int arr[], int low, int high);

B. int partition(int arr[], int low, int high);

C. int partition(int arr, int low, int high);

D. int partition(int arr[], int start, int end, int pivot);

Solution

1. Step 1: Identify correct parameter types

   The partition function takes an array and two indices low and high to work on a subarray.

2. Step 2: Check return type

   Partition returns an integer index where the pivot finally sits.

3. Final Answer:

   int partition(int arr[], int low, int high); -> Option B

4. Quick Check:

   Partition returns int index with arr[], low, high [OK]

Hint: Partition returns pivot index, takes array and two indices [OK]

Common Mistakes:

• Using void return type for partition
• Passing array as int instead of int[]
• Adding extra parameters like pivot unnecessarily

3. What will be the output array after one partition call on arr = [4, 7, 2, 9, 1] with low=0 and high=4 if pivot is chosen as last element?

medium

A. [1, 4, 2, 7, 9]

B. [4, 7, 2, 9, 1]

C. [1, 2, 7, 9, 4]

D. [1, 7, 2, 9, 4]

Solution

1. Step 1: Choose pivot and start partitioning

   Pivot is last element: 1. There are no elements less than 1.

2. Step 2: Rearrange array around pivot

   No swaps occur in the loop since all arr[j] > 1 for j = 0 to 3. Then swap arr[0] and arr[4], resulting in [1, 7, 2, 9, 4].

3. Final Answer:

   [1, 7, 2, 9, 4] -> Option D

4. Quick Check:

   Pivot 1 placed at position 0, all to right > 1 [OK]

Hint: Pivot last element, smaller left, larger right [OK]

Common Mistakes:

• Not moving pivot to correct position
• Swapping elements incorrectly
• Assuming pivot stays at end

4. Identify the error in this Quick Sort partition code snippet:

int partition(int arr[], int low, int high) {
  int pivot = arr[high];
  int i = low;
  for (int j = low; j < high; j++) {
    if (arr[j] < pivot) {
      swap(arr[i], arr[j]);
      i++;
    }
  }
  swap(arr[i], arr[high]);
  return i;
}

medium

A. Initialization of i should be low - 1

B. Loop should run until j <= high

C. Pivot should be arr[low] instead of arr[high]

D. Swap inside if should be swap(arr[j], arr[i])

Solution

1. Step 1: Check initialization of i

   i should start at low - 1 to track last smaller element index before loop.

2. Step 2: Understand loop and swaps

   Loop runs j from low to high-1 correctly; swapping arr[i+1] and arr[high] places pivot correctly.

3. Final Answer:

   Initialization of i should be low - 1 -> Option A

4. Quick Check:

   i = low - 1 needed for correct partition [OK]

Hint: i starts before low to track smaller elements [OK]

Common Mistakes:

• Starting i at low causes wrong swaps
• Loop running to high causes out-of-bound errors
• Changing pivot position unnecessarily

5. Given an array arr = [10, 80, 30, 90, 40, 50, 70], what is the state of the array after the first full Quick Sort partition step choosing the last element as pivot?

hard

A. [10, 30, 40, 50, 70, 80, 90]

B. [10, 30, 40, 50, 70, 90, 80]

C. [10, 80, 30, 90, 40, 50, 70]

D. [10, 30, 40, 50, 80, 90, 70]

Solution

1. Step 1: Identify pivot and partition

   Pivot is last element 70. Partition rearranges elements less than 70 to left.

2. Step 2: Rearrange array after partition

   Elements less than 70: 10, 30, 40, 50. Elements greater: 80, 90. After partition, pivot 70 placed after smaller elements: [10, 30, 40, 50, 70, 80, 90]

3. Final Answer:

   [10, 30, 40, 50, 70, 80, 90] -> Option A

4. Quick Check:

   Pivot 70 placed after smaller elements [OK]

Hint: Pivot last, smaller left, pivot placed next, larger right [OK]

Common Mistakes:

• Sorting entire array in first step
• Swapping pivot with wrong element
• Assuming pivot moves to last position