Record structs in C Sharp (C#) - Time & Space Complexity

Time Complexity: Record structs

O(n)

Understanding Time Complexity

When working with record structs, it's important to understand how their operations grow as the data size increases.

We want to know how fast the program runs when creating or comparing record structs as input grows.

Scenario Under Consideration

Analyze the time complexity of the following code snippet.

public record struct Point(int X, int Y);

public void ProcessPoints(Point[] points)
{
    foreach (var p in points)
    {
        var copy = p;
        var isOrigin = copy == new Point(0, 0);
    }
}
    

This code creates copies of record structs and compares each to a fixed point.

Identify Repeating Operations

Identify the loops, recursion, array traversals that repeat.

• Primary operation: Looping through each element in the array.
• How many times: Once for every point in the input array.

How Execution Grows With Input

Each point is copied and compared once, so the work grows directly with the number of points.

Input Size (n)	Approx. Operations
10	About 10 copies and 10 comparisons
100	About 100 copies and 100 comparisons
1000	About 1000 copies and 1000 comparisons

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

Final Time Complexity

Time Complexity: O(n)

This means the time to run grows in a straight line with the number of points.

Common Mistake

[X] Wrong: "Copying a record struct is expensive and slows down the program a lot."

[OK] Correct: Record structs are value types and copying them is usually very fast and done once per item, so it grows linearly, not exponentially.

Interview Connect

Understanding how record structs behave with copying and comparison helps you reason about performance in real applications, showing you can think about efficiency clearly.

Self-Check

"What if the record struct had many more fields? How would that affect the time complexity of copying and comparing?"