Container With Most Water in DSA C++ - Time & Space Complexity

Time Complexity: Container With Most Water

O(n)

Understanding Time Complexity

We want to understand how the time needed to find the container with the most water grows as the number of lines increases.

How does the number of operations change when we have more lines to check?

Scenario Under Consideration

Analyze the time complexity of the following code snippet.

int maxArea(std::vector<int>& height) {
    int left = 0, right = height.size() - 1;
    int max_area = 0;
    while (left < right) {
        int width = right - left;
        int area = std::min(height[left], height[right]) * width;
        max_area = std::max(max_area, area);
        if (height[left] < height[right]) {
            left++;
        } else {
            right--;
        }
    }
    return max_area;
}
    

This code finds the maximum water container by moving two pointers from both ends towards the center.

Identify Repeating Operations

Identify the loops, recursion, array traversals that repeat.

• Primary operation: The while loop that moves the left and right pointers towards each other.
• How many times: At most, the loop runs once for each element, so about n times where n is the number of lines.

How Execution Grows With Input

As the number of lines increases, the number of loop steps grows roughly the same as the number of lines.

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

Pattern observation: The operations grow linearly with input size.

Final Time Complexity

Time Complexity: O(n)

This means the time to find the max water container grows in direct proportion to the number of lines.

Common Mistake

[X] Wrong: "Because there are two pointers, the time complexity is O(n²) since we check pairs."

[OK] Correct: The pointers move inward only once each, so total steps are just n, not n squared.

Interview Connect

Understanding this linear time approach shows you can optimize from a naive double loop to a smart two-pointer method, a valuable skill in interviews.

Self-Check

"What if we used a nested loop to check all pairs instead of two pointers? How would the time complexity change?"

Practice

1. What is the main goal of the Container With Most Water problem?

easy

A. Find two lines that together with the x-axis form a container holding the most water

B. Sort the array of heights in ascending order

C. Find the maximum height in the array

D. Calculate the sum of all heights

Solution

1. Step 1: Understand the problem statement

   The problem asks to find two vertical lines which, together with the x-axis, form a container that holds the maximum amount of water.

2. Step 2: Identify what is being maximized

   The area between two lines is calculated by the minimum height of the two lines multiplied by the distance between them. We want to maximize this area.

3. Final Answer:

   Find two lines that together with the x-axis form a container holding the most water -> Option A

4. Quick Check:

   Goal = Max water container [OK]

Hint: Max area = min height * width between lines [OK]

Common Mistakes:

• Thinking it's about sorting heights
• Trying to sum heights instead of area
• Looking for max single height only

2. Which of the following C++ code snippets correctly initializes two pointers for the two-pointer approach in the Container With Most Water problem?

easy

A. int left = 1, right = heights.size();

B. int left = 0, right = heights.size() - 1;

C. int left = 0, right = heights.size();

D. int left = 1, right = heights.size() - 1;

Solution

1. Step 1: Understand pointer initialization

   We start with two pointers: one at the beginning (index 0) and one at the end (index size-1) of the array.

2. Step 2: Check each option

   int left = 0, right = heights.size() - 1; correctly sets left = 0 and right = size - 1, which are valid indices. Other options use invalid indices or off-by-one errors.

3. Final Answer:

   int left = 0, right = heights.size() - 1; -> Option B

4. Quick Check:

   Pointers start at ends = int left = 0, right = heights.size() - 1; [OK]

Hint: Start pointers at array ends: 0 and size-1 [OK]

Common Mistakes:

• Using size() as index (out of bounds)
• Starting pointers at 1 instead of 0
• Swapping left and right initialization

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

std::vector<int> heights = {1, 8, 6, 2, 5, 4, 8, 3, 7};
int left = 0, right = heights.size() - 1;
int maxArea = 0;
while (left < right) {
    int height = std::min(heights[left], heights[right]);
    int width = right - left;
    maxArea = std::max(maxArea, height * width);
    if (heights[left] < heights[right]) {
        left++;
    } else {
        right--;
    }
}
std::cout << maxArea << std::endl;

medium

A. 56

B. 50

C. 48

D. 49

Solution

1. Step 1: Trace the two-pointer approach

   Start with left=0 (height=1), right=8 (height=7), area= min(1,7)*8=8. Move left pointer since height[left]

2. Step 2: Continue updating maxArea

   Next left=1 (8), right=8 (7), area= min(8,7)*7=49 (maxArea=49). Move right pointer since height[left]>height[right]. Then left=1, right=7 (3), area= min(8,3)*6=18 (maxArea=49). Move right pointer. Continue similarly until pointers meet. The maximum area found is 49.

3. Final Answer:

   49 -> Option D

4. Quick Check:

   Max area = 49 [OK]

Hint: Move pointer at smaller height to find max area [OK]

Common Mistakes:

• Not updating maxArea correctly
• Moving wrong pointer after comparison
• Calculating area with max height instead of min

4. Identify the bug in the following code snippet for the Container With Most Water problem:

int maxArea(std::vector<int>& heights) {
    int left = 0, right = heights.size();
    int max_area = 0;
    while (left < right) {
        int height = std::min(heights[left], heights[right]);
        int width = right - left;
        max_area = std::max(max_area, height * width);
        if (heights[left] < heights[right]) {
            left++;
        } else {
            right--;
        }
    }
    return max_area;
}

medium

A. The loop condition should be left <= right

B. Use max instead of min to calculate height

C. right should be initialized to heights.size() - 1

D. Increment right instead of decrementing

Solution

1. Step 1: Check pointer initialization

   right is initialized to heights.size(), which is out of bounds since valid indices go up to size()-1.

2. Step 2: Correct initialization and loop condition

   right should be heights.size() - 1 to point to the last valid element. The loop condition left < right is correct.

3. Final Answer:

   right should be initialized to heights.size() - 1 -> Option C

4. Quick Check:

   Index out of bounds fixed by right should be initialized to heights.size() - 1 [OK]

Hint: Array indices go from 0 to size-1 [OK]

Common Mistakes:

• Using size() as index causing runtime error
• Changing loop condition incorrectly
• Using max instead of min for height

5. Given an array of heights representing vertical lines, how would you modify the two-pointer approach to find the maximum water container if the array can contain zero heights (lines with zero height)?

hard

A. Skip zero height lines by moving pointers inward until non-zero heights are found

B. Treat zero heights as normal and proceed with the standard two-pointer approach

C. Remove zero height lines from the array before processing

D. Use a nested loop to check all pairs instead of two-pointer

Solution

1. Step 1: Understand zero height impact

   Lines with zero height cannot hold water, so including them wastes time and area calculations.

2. Step 2: Modify two-pointer approach

   Skip zero height lines by moving pointers inward until both point to non-zero heights. Then apply the standard two-pointer logic to maximize area.

3. Final Answer:

   Skip zero height lines by moving pointers inward until non-zero heights are found -> Option A

4. Quick Check:

   Skip zeros for max area [OK]

Hint: Ignore zero heights by moving pointers inward [OK]

Common Mistakes:

• Processing zero height lines as normal
• Removing elements changes indices and complicates logic
• Switching to nested loops loses efficiency