Insertion Sort Algorithm in DSA Python - Time & Space Complexity

Time Complexity: Insertion Sort Algorithm

O(n²)

Understanding Time Complexity

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

Specifically, how many steps does it take to sort a list of numbers?

Scenario Under Consideration

Analyze the time complexity of the following Insertion Sort code.

for i in range(1, len(arr)):
    key = arr[i]
    j = i - 1
    while j >= 0 and arr[j] > key:
        arr[j + 1] = arr[j]
        j -= 1
    arr[j + 1] = key

This code sorts the list by inserting each element into its correct place among the sorted elements to its left.

Identify Repeating Operations

• 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.

How Execution Grows With Input

As the list size grows, the number of comparisons and shifts grows 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 list size roughly quadruples the work.

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 compare simple sorting methods and recognize when they are efficient or not.

Self-Check

"What if we changed the inner while loop to stop early when the list is already sorted? How would the time complexity change?"

Practice

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

easy

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

B. Divide the list into halves and sort each half separately

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

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

Solution

1. Step 1: Understand insertion sort process

   Insertion sort builds a sorted list by taking one element at a time and placing it in the correct position among the already sorted elements.

2. Step 2: Compare with other sorting methods

   Options A, B, and D describe other sorting algorithms: bubble sort, merge sort, and selection sort respectively.

3. Final Answer:

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

4. Quick Check:

   Insertion sort = Insert elements in order [OK]

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

Common Mistakes:

• Confusing insertion sort with bubble sort
• Thinking insertion sort divides the list
• Mixing insertion sort with selection sort

2. Which of the following is the correct syntax to start the outer loop for insertion sort on a list arr of length n in Python?

easy

A. for i in range(0, n-1):

B. for i in range(n):

C. for i in range(1, n):

D. for i in range(n-1, 0, -1):

Solution

1. Step 1: Identify insertion sort loop start

   The outer loop starts from index 1 because the first element (index 0) is considered sorted.

2. Step 2: Check options

   for i in range(1, n): correctly uses range(1, n). Options B and C start from 0 which is incorrect. for i in range(n-1, 0, -1): loops backwards which is not standard for insertion sort.

3. Final Answer:

   for i in range(1, n): -> Option C

4. Quick Check:

   Start loop at 1 for insertion sort [OK]

Hint: Start outer loop from 1, not 0 [OK]

Common Mistakes:

• Starting loop at 0 instead of 1
• Using reverse loop incorrectly
• Confusing loop ranges

3. What will be the output of the following code snippet?

def insertion_sort(arr):
    for i in range(1, len(arr)):
        key = arr[i]
        j = i - 1
        while j >= 0 and arr[j] > key:
            arr[j + 1] = arr[j]
            j -= 1
        arr[j + 1] = key

arr = [4, 3, 2, 1]
insertion_sort(arr)
print(arr)

medium

A. [4, 3, 2, 1]

B. [1, 2, 3, 4]

C. [1, 3, 2, 4]

D. [2, 3, 4, 1]

Solution

1. Step 1: Trace the insertion sort on input

   The list [4, 3, 2, 1] is sorted step-by-step by moving smaller elements leftwards until fully sorted.

2. Step 2: Final sorted list

   After sorting, the list becomes [1, 2, 3, 4].

3. Final Answer:

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

4. Quick Check:

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

Hint: Insertion sort outputs sorted ascending list [OK]

Common Mistakes:

• Assuming original list remains unchanged
• Confusing output with partial sorting
• Misreading the while loop condition

4. Find the error in the following insertion sort code:

def insertion_sort(arr):
    for i in range(1, len(arr)):
        key = arr[i]
        j = i
        while j > 0 and arr[j-1] > key:
            arr[j] = arr[j-1]
            j -= 1
        arr[j] = key

arr = [3, 1, 2]
insertion_sort(arr)
print(arr)

medium

A. The for loop should start from 0, not 1

B. The while loop condition should be j >= 0, not j > 0

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

D. The variable j should start at i - 1, not i

Solution

1. Step 1: Check initialization of j

   In insertion sort, j should start at i - 1 to compare the key with previous elements using the standard condition arr[j] > key.

2. Step 2: Verify other parts

   The while loop condition and assignment are correct. The for loop correctly starts at 1.

3. Final Answer:

   The variable j should start at i - 1, not i -> Option D

4. Quick Check:

   j = i - 1 to compare previous elements [OK]

Hint: Start j at i-1 to compare with previous elements [OK]

Common Mistakes:

• Using j = i instead of standard j = i-1
• Changing while loop condition incorrectly
• Misplacing key assignment inside loop

5. Given a list arr = [5, 3, 8, 6, 2], how many total shifts (element moves) will insertion sort perform to sort the list in ascending order?

hard

A. 6

B. 8

C. 7

D. 5

Solution

1. Step 1: Trace shifts during sorting

   Insertion sort shifts elements to insert the key in the correct place:
   - i=1 (key=3): shift 5 right (1 shift)
   - i=2 (key=8): no shift (0 shifts)
   - i=3 (key=6): shift 8 right (1 shift)
   - i=4 (key=2): shift 8, 6, 5, 3 right (4 shifts)

2. Step 2: Calculate total shifts

   Total shifts = 1 + 0 + 1 + 4 = 6 shifts. But note that each shift moves one element one position right. Counting carefully:
   At i=1: 1 shift
   At i=3: 1 shift
   At i=4: 4 shifts
   Total = 6 shifts

3. Step 3: Recount carefully

   Actually, at i=4, elements 3,5,6,8 are shifted right one by one (4 shifts). Total shifts = 1 + 0 + 1 + 4 = 6.

4. Final Answer:

   6 -> Option A

5. Quick Check:

   Count shifts per insertion = 6 [OK]

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

Common Mistakes:

• Counting comparisons instead of shifts
• Missing multiple shifts in one insertion
• Confusing shifts with swaps