Zip operation in C Sharp (C#) - Time & Space Complexity

Time Complexity: Zip operation

O(n)

Understanding Time Complexity

When we combine two lists element by element, it is important to know how the time to do this grows as the lists get bigger.

We want to find out how the work changes when the input lists grow in size.

Scenario Under Consideration

Analyze the time complexity of the following code snippet.

var list1 = new List<int> {1, 2, 3, 4};
var list2 = new List<string> {"a", "b", "c", "d"};

var zipped = list1.Zip(list2, (num, letter) => ($"{num}", letter)).ToList();

foreach (var pair in zipped)
{
    Console.WriteLine(pair);
}
    

This code pairs elements from two lists one by one and prints each pair.

Identify Repeating Operations

• Primary operation: The Zip method internally loops through both lists at the same time.
• How many times: It runs once for each element until the shorter list ends.

How Execution Grows With Input

As the lists get longer, the number of pairs created grows directly with the size of the smaller list.

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

Pattern observation: The work grows evenly as the input size grows.

Final Time Complexity

Time Complexity: O(n)

This means the time to zip grows in a straight line with the size of the smaller list.

Common Mistake

[X] Wrong: "Zipping two lists takes time based on both lists multiplied together."

[OK] Correct: Zip stops when the shorter list ends, so it only runs as many times as the smaller list length, not the product of both.

Interview Connect

Understanding how combining two lists works helps you explain efficiency clearly and shows you can think about how code scales in real projects.

Self-Check

"What if we zipped three lists instead of two? How would the time complexity change?"