Insertion Sort Algorithm in DSA C++ - Time & Space Complexity

Time Complexity: Insertion Sort Algorithm

O(n²)

Understanding Time Complexity

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

How does the number of steps increase when sorting more items?

Scenario Under Consideration

Analyze the time complexity of the following code snippet.

void insertionSort(int arr[], int n) {
  for (int i = 1; i < n; i++) {
    int key = arr[i];
    int j = i - 1;
    while (j >= 0 && arr[j] > key) {
      arr[j + 1] = arr[j];
      j--;
    }
    arr[j + 1] = key;
  }
}
    

This code sorts an array by inserting each element into its correct position among the previously sorted elements.

Identify Repeating Operations

Identify the loops, recursion, array traversals that repeat.

• Primary operation: The inner while loop that shifts elements to insert the key.
• How many times: The outer for loop runs n-1 times, and the inner while loop can run up to i times for each i from 1 to n-1.

How Execution Grows With Input

As the list size grows, the number of comparisons and shifts increases roughly with the square of the size in the worst case.

Input Size (n)	Approx. Operations
10	About 45 comparisons and shifts
100	About 4,950 comparisons and shifts
1000	About 499,500 comparisons and shifts

Pattern observation: The operations grow roughly by the square of the input size, so doubling the input makes the work about four times bigger.

Final Time Complexity

Time Complexity: O(n²)

This means the time taken grows roughly with the square of the number of items to sort.

Common Mistake

[X] Wrong: "Insertion Sort always takes the same time no matter the input order."

[OK] Correct: If the list is already mostly sorted, Insertion Sort runs much faster, closer to linear time, because fewer shifts are needed.

Interview Connect

Understanding Insertion Sort's time complexity helps you explain sorting basics clearly and compare simple algorithms to more advanced ones.

Self-Check

"What if we changed the array to be nearly sorted? How would the time complexity change?"

Practice

1. What is the main idea behind the Insertion Sort algorithm?

easy

A. Divide the array into halves and sort each half recursively

B. Swap adjacent elements if they are in the wrong order repeatedly

C. Build the sorted array one element at a time by inserting elements in their correct position

D. Select the smallest element and swap it with the first unsorted element

Solution

1. Step 1: Understand the insertion process

   Insertion sort takes one element at a time and inserts it into the correct position in the already sorted part of the array.

2. Step 2: Compare with other sorting methods

   Unlike divide and conquer (merge sort) or swapping adjacent elements (bubble sort), insertion sort builds the sorted array gradually by insertion.

3. Final Answer:

   Build the sorted array one element at a time by inserting elements in their correct position -> Option C

4. Quick Check:

   Insertion sort = Insert elements correctly one by one [OK]

Hint: Insertion sort inserts elements step-by-step in order [OK]

Common Mistakes:

• Confusing insertion sort with bubble sort
• Thinking it divides array like merge sort
• Assuming it swaps only smallest elements

2. Which of the following is the correct syntax for the inner loop condition in insertion sort in C++?

easy

A. for (int j = i + 1; j < n && arr[j] < key; j++)

B. for (int j = i - 1; j >= 0 && arr[j] > key; j--)

C. for (int j = 0; j < i && arr[j] < key; j++)

D. for (int j = i - 1; j >= 0 && arr[j] < key; j--)

Solution

1. Step 1: Identify the inner loop role

   The inner loop moves backward from the current element's previous index, shifting elements greater than the key to the right.

2. Step 2: Match the correct loop condition

   The loop continues while j >= 0 and arr[j] > key, decrementing j each time.

3. Final Answer:

   for (int j = i - 1; j >= 0 && arr[j] > key; j--) -> Option B

4. Quick Check:

   Inner loop moves backward while arr[j] > key [OK]

Hint: Inner loop moves backward while element is greater than key [OK]

Common Mistakes:

• Using j++ instead of j-- in inner loop
• Checking arr[j] < key instead of > key
• Starting inner loop from wrong index

3. What will be the output array after running insertion sort on arr = {4, 3, 2, 1}?

medium

A. [2, 3, 4, 1]

B. [4, 3, 2, 1]

C. [1, 3, 2, 4]

D. [1, 2, 3, 4]

Solution

1. Step 1: Trace first iteration

   Insert 3 into sorted part {4}: shift 4 right, array becomes {3,4,2,1}.

2. Step 2: Trace second iteration

   Insert 2 into {3,4}: shift 4 and 3 right, array becomes {2,3,4,1}.

3. Step 3: Trace third iteration

   Insert 1 into {2,3,4}: shift all right, array becomes {1,2,3,4}.

4. Final Answer:

   [1, 2, 3, 4] -> Option D

5. Quick Check:

   Sorted ascending = [1, 2, 3, 4] [OK]

Hint: Insertion sort sorts ascending by shifting larger elements right [OK]

Common Mistakes:

• Assuming array stays same if reversed
• Stopping after first iteration
• Not shifting all larger elements

4. Identify the error in this insertion sort snippet:

for (int i = 1; i < n; i++) {
  int key = arr[i];
  int j = i - 1;
  while (j >= 0 && arr[j] < key) {
    arr[j + 1] = arr[j];
    j--;
  }
  arr[j + 1] = key;
}

medium

A. The comparison in while should be arr[j] > key, not arr[j] < key

B. The loop should start from i = 0 instead of i = 1

C. The assignment arr[j + 1] = key should be outside the loop

D. The decrement j-- should be j++ inside the while loop

Solution

1. Step 1: Understand the while loop condition

   Insertion sort shifts elements greater than key to the right, so condition must be arr[j] > key.

2. Step 2: Identify the incorrect comparison

   Current code uses arr[j] < key, which shifts smaller elements incorrectly, breaking sorting.

3. Final Answer:

   The comparison in while should be arr[j] > key, not arr[j] < key -> Option A

4. Quick Check:

   Shift elements greater than key, so condition is arr[j] > key [OK]

Hint: While loop compares arr[j] > key to shift larger elements [OK]

Common Mistakes:

• Using wrong comparison sign in while condition
• Starting loop from wrong index
• Misplacing key assignment inside loop

5. Given an array arr = {5, 2, 9, 1, 5, 6}, how many total shifts (element moves) will insertion sort perform to sort it?

hard

A. 6

B. 7

C. 10

D. 5

Solution

1. Step 1: Insert 2 into {5}

   Shift 5 right (1 shift). Array: {2, 5, 9, 1, 5, 6}

2. Step 2: Insert 9 into {2, 5}

   No shift needed since 9 > 5 (0 shifts).

3. Step 3: Insert 1 into {2, 5, 9}

   Shift 9, 5, 2 right (3 shifts). Array: {1, 2, 5, 9, 5, 6}

4. Step 4: Insert 5 into {1, 2, 5, 9}

   Shift 9 right (1 shift, stops at 5 == 5). Array: {1, 2, 5, 5, 9, 6}

5. Step 5: Insert 6 into {1, 2, 5, 5, 9}

   Shift 9 right (1 shift). Array: {1, 2, 5, 5, 6, 9}

6. Final Answer:

   6 -> Option A

7. Quick Check:

   Total shifts = 1 + 0 + 3 + 1 + 1 = 6 [OK]

Hint: Count shifts by tracing each insertion carefully [OK]

Common Mistakes:

• Counting only swaps, not shifts
• Missing shifts for repeated elements
• Confusing key placement with shifts