Two Pointer Technique on Arrays in DSA Python - Time & Space Complexity

Time Complexity: Two Pointer Technique on Arrays

O(n)

Understanding Time Complexity

We want to understand how fast the two pointer technique works when scanning arrays.

How does the number of steps grow as the array gets bigger?

Scenario Under Consideration

Analyze the time complexity of the following code snippet.

def two_pointer_example(arr, target):
    left = 0
    right = len(arr) - 1
    while left < right:
        current_sum = arr[left] + arr[right]
        if current_sum == target:
            return True
        elif current_sum < target:
            left += 1
        else:
            right -= 1
    return False

This code checks if any two numbers in a sorted array add up to a target value using two pointers.

Identify Repeating Operations

• Primary operation: The while loop moves the left and right pointers through the array.
• How many times: Each pointer moves at most from one end to the other, so together they move at most n steps.

How Execution Grows With Input

As the array size grows, the total steps grow roughly in a straight line with the number of elements.

Input Size (n)	Approx. Operations
10	About 10 steps
100	About 100 steps
1000	About 1000 steps

Pattern observation: The steps increase directly with input size, not faster or slower.

Final Time Complexity

Time Complexity: O(n)

This means the time to run grows in a straight line with the size of the array.

Common Mistake

[X] Wrong: "The two pointer method checks every pair, so it must be O(n²)."

[OK] Correct: The pointers move inward without repeating pairs, so total steps are only about n, not n squared.

Interview Connect

Understanding this technique shows you can solve problems efficiently by scanning arrays smartly, a skill many interviews value.

Self-Check

"What if the array was not sorted? How would the time complexity change if we still tried this two pointer approach?"

Practice

1. What is the main idea behind the Two Pointer Technique when used on arrays?

easy

A. Use two arrays to store temporary results

B. Sort the array twice before processing

C. Use two indices to scan the array from different ends or positions simultaneously

D. Use recursion to divide the array into two parts

Solution

1. Step 1: Understand the two pointer concept

   The technique uses two pointers (indices) to traverse the array, often starting from opposite ends or different positions.

2. Step 2: Recognize the purpose

   This helps solve problems efficiently by reducing the number of iterations compared to nested loops.

3. Final Answer:

   Use two indices to scan the array from different ends or positions simultaneously -> Option C

4. Quick Check:

   Two pointers scan array ends or positions [OK]

Hint: Think of two fingers moving inward or outward on the array [OK]

Common Mistakes:

• Confusing two pointers with using two separate arrays
• Assuming sorting is always required
• Thinking recursion is part of two pointer technique

2. Which of the following is the correct syntax to initialize two pointers left and right for an array arr in Python?

easy

A. left = 0; right = len(arr) - 1

B. left = 1; right = len(arr)

C. left = -1; right = len(arr)

D. left = 0; right = len(arr)

Solution

1. Step 1: Identify valid pointer positions

   In Python, array indices start at 0, so the left pointer should start at 0.

2. Step 2: Set right pointer correctly

   The right pointer should be at the last valid index, which is length of array minus 1.

3. Final Answer:

   left = 0; right = len(arr) - 1 -> Option A

4. Quick Check:

   Start left at 0 and right at last index [OK]

Hint: Remember Python arrays start at 0, last index is length-1 [OK]

Common Mistakes:

• Setting right pointer to len(arr) causes index error
• Starting left pointer at 1 misses first element
• Using negative indices incorrectly

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

arr = [1, 3, 5, 7, 9]
left, right = 0, 4
result = []
while left < right:
    result.append(arr[left] + arr[right])
    left += 1
    right -= 1
print(result)

medium

A. [10, 14]

B. [10, 12]

C. [10, 12, 14]

D. [10, 10]

Solution

1. Step 1: Trace the loop iterations

   Initial pointers: left=0, right=4 - Iteration 1: arr[0]+arr[4] = 1+9=10, result=[10] - left=1, right=3 - Iteration 2: arr[1]+arr[3] = 3+7=10, result=[10,10] - left=2, right=2 (loop ends because left is not less than right)

2. Step 2: Check loop condition and final result

   Loop stops when left == right (2), so only two sums added: [10, 10]

3. Final Answer:

   [10, 10] -> Option D

4. Quick Check:

   Sum pairs from ends until pointers meet [OK]

Hint: Add pairs from ends until pointers cross [OK]

Common Mistakes:

• Including middle element sum when pointers meet
• Not updating pointers correctly
• Confusing indices causing wrong sums

4. Find the error in the following code that uses two pointers to check if an array is a palindrome:

def is_palindrome(arr):
    left, right = 0, len(arr)
    while left < right:
        if arr[left] != arr[right]:
            return False
        left += 1
        right -= 1
    return True

print(is_palindrome([1, 2, 3, 2, 1]))

medium

A. left should start at 1

B. right should be initialized as len(arr) - 1

C. Use 'while left <= right' instead of 'while left < right'

D. Return True should be inside the loop

Solution

1. Step 1: Check pointer initialization

   In Python, last index is len(arr) - 1, but code sets right = len(arr), which is out of range.

2. Step 2: Correct pointer initialization

   Change right to len(arr) - 1 to avoid index error and correctly compare elements.

3. Final Answer:

   right should be initialized as len(arr) - 1 -> Option B

4. Quick Check:

   Last index = length - 1 [OK]

Hint: Last index is length minus one, not length [OK]

Common Mistakes:

• Setting right pointer to length causes index error
• Changing loop condition incorrectly
• Returning True too early inside loop

5. Given a sorted array arr and a target sum target, how can you use the two pointer technique to find if there exists two numbers that add up to target? Choose the correct approach.

hard

A. Initialize left at 0 and right at len(arr)-1; move pointers inward based on sum comparison

B. Initialize both pointers at 0 and move right pointer only

C. Sort the array again and use binary search for each element

D. Use two nested loops to check all pairs

Solution

1. Step 1: Set pointers at array ends

   Start left pointer at 0 (start) and right pointer at last index (len(arr)-1).

2. Step 2: Move pointers based on sum

   Calculate sum of arr[left] + arr[right]. If sum equals target, return True. If sum is less, move left pointer right to increase sum. If sum is more, move right pointer left to decrease sum.

3. Final Answer:

   Initialize left at 0 and right at len(arr)-1; move pointers inward based on sum comparison -> Option A

4. Quick Check:

   Two pointers from ends adjust to find target sum [OK]

Hint: Move left/right pointers based on sum compared to target [OK]

Common Mistakes:

• Moving only one pointer without condition
• Using nested loops instead of two pointers
• Not starting pointers at array ends