Counting Sort Algorithm in DSA Javascript - Time & Space Complexity

Time Complexity: Counting Sort Algorithm

O(n + k)

Understanding Time Complexity

Counting Sort is a special sorting method that works well when numbers are in a small range.

We want to understand how the time it takes grows as the list size and number range grow.

Scenario Under Consideration

Analyze the time complexity of the following code snippet.

function countingSort(arr) {
  const max = Math.max(...arr);
  const count = new Array(max + 1).fill(0);
  for (const num of arr) {
    count[num]++;
  }
  let sortedIndex = 0;
  for (let i = 0; i < count.length; i++) {
    while (count[i] > 0) {
      arr[sortedIndex++] = i;
      count[i]--;
    }
  }
  return arr;
}
    

This code sorts an array by counting how many times each number appears, then rebuilding the sorted array.

Identify Repeating Operations

Identify the loops, recursion, array traversals that repeat.

• Primary operation: Counting each number in the input array and then rebuilding the sorted array.
• How many times: The first loop runs once for each element in the input (n times). The second loop runs once for each number in the range (k times), and inside it, the inner loop runs as many times as the count of that number.

How Execution Grows With Input

Explain the growth pattern intuitively.

Input Size (n)	Range Size (k)	Approx. Operations
10	5	About 10 + 5 = 15 operations
100	20	About 100 + 20 = 120 operations
1000	100	About 1000 + 100 = 1100 operations

Pattern observation: The time grows roughly with the sum of the input size and the range size.

Final Time Complexity

Time Complexity: O(n + k)

This means the time grows linearly with both the number of items and the range of numbers.

Common Mistake

[X] Wrong: "Counting Sort always runs in linear time regardless of the number range."

[OK] Correct: If the range of numbers (k) is very large compared to the input size (n), the time depends on k too, so it can be slower.

Interview Connect

Understanding Counting Sort's time complexity helps you choose the right sorting method based on data size and range, a useful skill in real coding tasks.

Self-Check

"What if the input array contains negative numbers? How would the time complexity change?"

Practice

1. What is the main idea behind the Counting Sort Algorithm?

easy

A. Swap adjacent elements if they are in wrong order repeatedly

B. Compare each element with every other element to sort

C. Count the occurrences of each element and use counts to place elements in order

D. Divide the array into halves and sort recursively

Solution

1. Step 1: Understand Counting Sort principle

   Counting sort counts how many times each value appears in the input array.

2. Step 2: Use counts to place elements

   Using these counts, it calculates positions to place each element in the sorted output.

3. Final Answer:

   Count the occurrences of each element and use counts to place elements in order -> Option C

4. Quick Check:

   Counting elements = Counting Sort [OK]

Hint: Counting sort counts elements, no comparisons needed [OK]

Common Mistakes:

• Thinking counting sort compares elements like bubble sort
• Confusing counting sort with divide and conquer methods
• Assuming counting sort works on all data types

2. Which of the following is the correct way to initialize the count array in Counting Sort for input array arr with maximum value maxVal in JavaScript?

easy

A. const count = new Array().fill(maxVal + 1);

B. const count = new Array(maxVal).fill(0);

C. const count = new Array(arr.length).fill(0);

D. const count = new Array(maxVal + 1).fill(0);

Solution

1. Step 1: Determine size of count array

   The count array must cover all values from 0 to maxVal, so size is maxVal + 1.

2. Step 2: Initialize count array with zeros

   Use new Array(maxVal + 1).fill(0) to create and fill with zeros.

3. Final Answer:

   const count = new Array(maxVal + 1).fill(0); -> Option D

4. Quick Check:

   Count array size = maxVal + 1 [OK]

Hint: Count array length = max value + 1 [OK]

Common Mistakes:

• Using maxVal instead of maxVal + 1 for array size
• Using input array length instead of maxVal
• Incorrectly filling array with maxVal + 1 instead of zeros

3. What will be the output of the following JavaScript code using Counting Sort?

function countingSort(arr) {
  const maxVal = Math.max(...arr);
  const count = new Array(maxVal + 1).fill(0);
  for (const num of arr) count[num]++;
  let sorted = [];
  for (let i = 0; i <= maxVal; i++) {
    while (count[i] > 0) {
      sorted.push(i);
      count[i]--;
    }
  }
  return sorted;
}

console.log(countingSort([4, 2, 2, 8, 3, 3, 1]));

medium

A. [1, 2, 2, 3, 3, 4, 8]

B. [8, 4, 3, 3, 2, 2, 1]

C. [1, 2, 3, 4, 8]

D. [4, 2, 2, 8, 3, 3, 1]

Solution

1. Step 1: Count occurrences of each number

   Count array after counting: count[1]=1, count[2]=2, count[3]=2, count[4]=1, count[8]=1.

2. Step 2: Build sorted array using counts

   Push each number count[i] times in ascending order: 1, 2, 2, 3, 3, 4, 8.

3. Final Answer:

   [1, 2, 2, 3, 3, 4, 8] -> Option A

4. Quick Check:

   Sorted array matches counting sort output [OK]

Hint: Counting sort output is sorted array with duplicates in order [OK]

Common Mistakes:

• Returning original array instead of sorted
• Reversing order by mistake
• Missing duplicates in output

4. Identify the bug in this Counting Sort implementation and select the fix:

function countingSort(arr) {
  const maxVal = Math.max(...arr);
  const count = new Array(maxVal).fill(0);
  for (const num of arr) {
    count[num]++;
  }
  let sorted = [];
  for (let i = 0; i < maxVal; i++) {
    while (count[i] > 0) {
      sorted.push(i);
      count[i]--;
    }
  }
  return sorted;
}

medium

A. Change count array size to maxVal + 1 and loop to i <= maxVal

B. Initialize count array with zeros using fill(1)

C. Use for loop from i = 1 to maxVal instead of 0

D. Remove the while loop and use if condition instead

Solution

1. Step 1: Check count array size and loop range

   Count array size is maxVal but should be maxVal + 1 to include maxVal index.

2. Step 2: Fix loop to include maxVal index

   Loop should run from 0 to maxVal inclusive (i <= maxVal) to cover all counts.

3. Final Answer:

   Change count array size to maxVal + 1 and loop to i <= maxVal -> Option A

4. Quick Check:

   Count array size and loop range must match maxVal + 1 [OK]

Hint: Count array size = maxVal + 1; loop to i <= maxVal [OK]

Common Mistakes:

• Using wrong count array size causing index errors
• Looping less than needed, missing maxVal counts
• Changing fill value incorrectly

5. Given an array arr = [5, 3, 0, 2, 3, 5, 1], how would you modify Counting Sort to sort only the elements between 1 and 4 inclusive, ignoring others?

hard

A. Use counting sort on full range but skip pushing elements outside 1 to 4

B. Count only elements between 1 and 4, then output sorted elements in that range

C. Sort entire array normally and then remove elements outside 1 to 4

D. Filter array first, then apply counting sort on filtered array

Solution

1. Step 1: Count only elements in range 1 to 4

   Ignore elements outside 1 to 4 while counting to focus sorting on this range.

2. Step 2: Output sorted elements only in that range

   Build sorted array using counts only for values 1 to 4, ignoring others.

3. Final Answer:

   Count only elements between 1 and 4, then output sorted elements in that range -> Option B

4. Quick Check:

   Counting and output limited to range [1,4] [OK]

Hint: Count and output only target range elements [OK]

Common Mistakes:

• Sorting full array then filtering, wasting effort
• Counting full range but skipping output incorrectly
• Filtering after sorting instead of before