Quick Sort as Divide and Conquer in DSA Javascript - Time & Space Complexity

Time Complexity: Quick Sort as Divide and Conquer

O(n log n)

Understanding Time Complexity

We want to understand how the time taken by Quick Sort changes as the list size grows.

How does dividing and sorting parts affect the total work done?

Scenario Under Consideration

Analyze the time complexity of the following Quick Sort code.

function quickSort(arr) {
  if (arr.length <= 1) return arr;
  const pivot = arr[arr.length - 1];
  const left = [];
  const right = [];
  for (let i = 0; i < arr.length - 1; i++) {
    if (arr[i] < pivot) left.push(arr[i]);
    else right.push(arr[i]);
  }
  return [...quickSort(left), pivot, ...quickSort(right)];
}
    

This code sorts an array by picking a pivot, splitting the array into smaller parts, and sorting those parts recursively.

Identify Repeating Operations

Look for loops and recursive calls that repeat work.

• Primary operation: Looping through the array to split it around the pivot.
• How many times: This splitting happens at each recursive call on smaller parts.

How Execution Grows With Input

Each time, the array is split and sorted recursively, so the work depends on how balanced the splits are.

Input Size (n)	Approx. Operations
10	About 30 to 50 operations
100	About 700 to 1000 operations
1000	About 10,000 to 15,000 operations

Pattern observation: The operations grow a bit faster than linear but much slower than quadratic, depending on how the array splits.

Final Time Complexity

Time Complexity: O(n log n)

This means the time grows a little more than linearly as the list gets bigger, thanks to dividing the problem into smaller parts.

Common Mistake

[X] Wrong: "Quick Sort always takes quadratic time because it uses loops inside recursion."

[OK] Correct: The splitting usually divides the array well, so the total work adds up to n log n, not n squared.

Interview Connect

Understanding Quick Sort's time complexity shows you can analyze divide and conquer methods, a key skill for many coding challenges.

Self-Check

"What if the pivot always picked the smallest element? How would the time complexity change?"

Practice

1. What is the main idea behind the Quick Sort algorithm in the divide and conquer approach?

easy

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

B. Sort the array by repeatedly swapping adjacent elements

C. Use extra space to merge two sorted arrays

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 based on a pivot, sorts each part recursively.

2. Step 2: Compare with other sorting methods

   Unlike bubble or selection sort, Quick Sort uses division and recursion, not just swapping or selecting smallest.

3. Final Answer:

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

4. Quick Check:

   Quick Sort = Divide and conquer [OK]

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

Common Mistakes:

• Confusing Quick Sort with bubble or selection sort
• Thinking Quick Sort merges arrays like merge sort
• Ignoring the pivot selection step

2. Which of the following is the correct syntax to choose a pivot element in a Quick Sort function in JavaScript?

easy

A. const pivot = arr.push();

B. const pivot = arr.length;

C. const pivot = arr.sort();

D. const pivot = arr[0];

Solution

1. Step 1: Identify how to select pivot in Quick Sort

   The pivot is usually an element from the array, often the first or last element.

2. Step 2: Check each option's correctness

   const pivot = arr[0]; selects the first element as pivot correctly. Others use wrong methods or properties.

3. Final Answer:

   const pivot = arr[0]; -> Option D

4. Quick Check:

   Pivot selection = arr[0] [OK]

Hint: Pivot is an element, not array length or method result [OK]

Common Mistakes:

• Using array length as pivot
• Calling array methods instead of accessing element
• Confusing pivot with sorted array

3. What will be the output of the following JavaScript Quick Sort partition step?

const arr = [4, 2, 7, 1];
const pivot = arr[0]; // 4
let left = [];
let right = [];
for(let i = 1; i < arr.length; i++) {
  if(arr[i] <= pivot) left.push(arr[i]);
  else right.push(arr[i]);
}
console.log(left);
console.log(right);

medium

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

B. [7] and [2, 1]

C. [2, 1] and [7]

D. [1, 2, 4] and []

Solution

1. Step 1: Identify pivot and partition logic

   Pivot is 4. Elements less or equal to 4 go to left, others to right.

2. Step 2: Partition the array

   Elements: 2 <= 4 -> left, 7 > 4 -> right, 1 <= 4 -> left. So left = [2,1], right = [7].

3. Final Answer:

   [2, 1] and [7] -> Option C

4. Quick Check:

   Partition by pivot 4 = [2,1] left, [7] right [OK]

Hint: Compare each element to pivot, separate into left/right [OK]

Common Mistakes:

• Including pivot in left or right arrays
• Mixing up less than and greater than conditions
• Forgetting to start loop from index 1

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

function partition(arr) {
  const pivot = arr[0];
  let left = [];
  let right = [];
  for(let i = 0; i < arr.length; i++) {
    if(arr[i] < pivot) left.push(arr[i]);
    else right.push(arr[i]);
  }
  return [...left, pivot, ...right];
}

medium

A. Use arr[i] <= pivot in condition instead of <

B. Loop should start from 1 to avoid including pivot twice

C. Pivot should be last element, not first

D. Return statement should not use spread operator

Solution

1. Step 1: Analyze loop range and pivot usage

   The loop starts at 0, so pivot element arr[0] is included in left or right arrays again.

2. Step 2: Correct loop start index

   Loop should start at 1 to skip pivot element and avoid duplication.

3. Final Answer:

   Loop should start from 1 to avoid including pivot twice -> Option B

4. Quick Check:

   Loop index = 1 to exclude pivot [OK]

Hint: Start loop after pivot index to avoid duplicates [OK]

Common Mistakes:

• Starting loop at 0 causing pivot duplication
• Changing pivot position unnecessarily
• Misunderstanding spread operator usage

5. Given the array [3, 6, 8, 10, 1, 2, 1], what is the correct sorted array after applying Quick Sort fully?

hard

A. [1, 1, 2, 3, 6, 8, 10]

B. [1, 2, 3, 6, 8, 10]

C. [3, 6, 8, 10, 1, 2, 1]

D. [10, 8, 6, 3, 2, 1, 1]

Solution

1. Step 1: Understand Quick Sort fully sorts the array

   Quick Sort recursively partitions and sorts all parts until fully sorted.

2. Step 2: Sort the array manually

   Sorted array is [1, 1, 2, 3, 6, 8, 10], including duplicates in order.

3. Final Answer:

   [1, 1, 2, 3, 6, 8, 10] -> Option A

4. Quick Check:

   Quick Sort output = sorted array ascending [OK]

Hint: Quick Sort returns fully sorted array ascending [OK]

Common Mistakes:

• Ignoring duplicate elements
• Confusing sorted with original array
• Thinking Quick Sort reverses array