Two Pointer Technique on Arrays in DSA C++ - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is the Two Pointer Technique on Arrays?

It is a method where two pointers move through the array to solve problems efficiently, often from different ends or positions, reducing time complexity.

beginner

In the Two Pointer Technique, what is a common use case when the array is sorted?

To find pairs or triplets with a specific sum by moving pointers inward from both ends to find matching values.

beginner

How do the two pointers typically move in the Two Pointer Technique?

One pointer usually starts at the beginning and the other at the end, and they move towards each other based on conditions.

intermediate

Why is the Two Pointer Technique more efficient than nested loops in some array problems?

Because it reduces the time complexity from O(n²) to O(n) by avoiding unnecessary repeated checks.

beginner

Give an example problem where the Two Pointer Technique is useful.

Finding if there exists two numbers in a sorted array that add up to a target sum.

What is the initial position of pointers in the Two Pointer Technique for a sorted array?

A Both at start

B One at start, one at end

C Both at end

D Random positions

Typically, one pointer starts at the beginning and the other at the end to efficiently check pairs.

What is the main advantage of using the Two Pointer Technique over nested loops?

A Lower time complexity

B Simpler code

C Uses more memory

D Works only on unsorted arrays

It reduces time complexity from O(n²) to O(n) by smartly moving pointers.

In a Two Pointer approach, if the sum of elements at pointers is less than the target, what should you do?

A Move the right pointer left

B Move both pointers

C Stop the process

D Move the left pointer right

Moving the left pointer right increases the sum since the array is sorted.

Which of these problems is best solved using the Two Pointer Technique?

A Finding duplicates in an unsorted array

B Sorting an array

C Finding pairs with a given sum in a sorted array

D Finding maximum element

Two Pointer Technique is ideal for pair sum problems in sorted arrays.

What is the time complexity of the Two Pointer Technique on arrays?

A O(n)

B O(n log n)

C O(log n)

D O(n²)

The technique usually runs in linear time O(n) by moving pointers through the array once.

Explain how the Two Pointer Technique works on a sorted array to find two numbers that add up to a target.

Think about how to adjust pointers to get closer to the target sum.

Describe why the Two Pointer Technique is more efficient than nested loops for certain array problems.

Focus on how the technique reduces repeated work.

Practice

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

easy

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

B. Use two nested loops to compare every pair of elements

C. Sort the array first and then use binary search

D. Use a single pointer to iterate through the array

Solution

1. Step 1: Understand the technique

   The Two Pointer Technique uses two indices to traverse the array, often from opposite ends or different positions, to solve problems efficiently.

2. Step 2: Compare with other options

   Options B and C describe different methods, and D uses only one pointer, so they do not match the Two Pointer Technique.

3. Final Answer:

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

4. Quick Check:

   Two pointers = two indices scanning array [OK]

Hint: Two pointers move independently to cover array efficiently [OK]

Common Mistakes:

• Thinking it always requires sorting first
• Confusing with nested loops approach
• Using only one pointer instead of two

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

easy

A. int left = n - 1, right = 0;

B. int left = 1, right = n;

C. int left = n, right = 0;

D. int left = 0, right = n - 1;

Solution

1. Step 1: Understand pointer initialization

   For two pointers scanning from start and end, left starts at 0 and right at n-1 (last index).

2. Step 2: Check each option

   int left = 0, right = n - 1; correctly sets left=0 and right=n-1. Options A, B, and C have incorrect indices that may cause out-of-bound errors.

3. Final Answer:

   int left = 0, right = n - 1; -> Option D

4. Quick Check:

   Start = 0, End = n-1 [OK]

Hint: Start left at 0 and right at n-1 for full array scan [OK]

Common Mistakes:

• Setting right pointer to n (out of bounds)
• Swapping left and right initial values
• Starting left pointer at 1 instead of 0

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

int arr[] = {1, 2, 3, 4, 5, 6};
int left = 0, right = 5;
int sum = 0;
while (left < right) {
    sum += arr[left] + arr[right];
    left++;
    right--;
}
std::cout << sum << std::endl;

medium

A. 27

B. 18

C. 21

D. 15

Solution

1. Step 1: Trace the loop iterations

   Initial pointers: left=0, right=5
   Iteration 1: sum=0+arr[0]+arr[5]=0+1+6=7, left=1, right=4
   Iteration 2: sum=7+arr[1]+arr[4]=7+2+5=14, left=2, right=3
   Iteration 3: sum=14+arr[2]+arr[3]=14+3+4=21, left=3, right=2 (loop ends)

2. Step 2: Final sum value

   Sum after loop is 21.

3. Final Answer:

   21 -> Option C

4. Quick Check:

   Sum pairs (1+6)+(2+5)+(3+4) = 21 [OK]

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

Common Mistakes:

• Including middle element when pointers cross
• Adding elements twice
• Incorrect loop condition (<= instead of <)

4. Identify the error in the following code that uses the two pointer technique to find if a sorted array contains two numbers that sum to a target value.

bool hasPairSum(int arr[], int n, int target) {
    int left = 0, right = n - 1;
    while (left <= right) {
        int sum = arr[left] + arr[right];
        if (sum == target) return true;
        else if (sum < target) left++;
        else right--;
    }
    return false;
}

medium

A. The loop condition should be left < right instead of left <= right

B. The pointers should be initialized as left = 1 and right = n

C. The sum calculation should be arr[left] - arr[right]

D. The function should return false inside the loop

Solution

1. Step 1: Analyze loop condition

   The loop runs while left <= right, which allows pointers to be equal, causing sum of same element twice.

2. Step 2: Correct loop condition

   Changing condition to left < right ensures pointers do not overlap, avoiding incorrect sum calculation.

3. Final Answer:

   The loop condition should be left < right instead of left <= right -> Option A

4. Quick Check:

   Pointers must not cross or overlap [OK]

Hint: Use left < right to avoid using same element twice [OK]

Common Mistakes:

• Allowing pointers to be equal causing wrong sums
• Incorrect pointer initialization
• Returning false too early inside loop

5. Given a sorted array arr of size n, how can you use the two pointer technique to find all unique pairs that sum up to a target value t? Which approach is correct?

hard

A. Use nested loops to check every pair and store unique pairs in a set

B. Initialize left = 0 and right = n - 1, move pointers inward, skip duplicates after finding a pair

C. Sort the array, then use binary search for each element to find complement

D. Initialize left = 1 and right = n, move pointers outward

Solution

1. Step 1: Set pointers and move inward

   Start with left at 0 and right at n-1. Move pointers inward based on sum compared to target.

2. Step 2: Skip duplicates to find unique pairs

   After finding a pair, increment left and decrement right while skipping duplicate values to avoid repeated pairs.

3. Final Answer:

   Initialize left = 0 and right = n - 1, move pointers inward, skip duplicates after finding a pair -> Option B

4. Quick Check:

   Two pointers inward + skip duplicates = unique pairs [OK]

Hint: Skip duplicates after finding pairs to avoid repeats [OK]

Common Mistakes:

• Not skipping duplicates causing repeated pairs
• Using nested loops causing higher time complexity
• Incorrect pointer initialization or movement