Function declaration syntax in Kotlin - Time & Space Complexity

Time Complexity: Function declaration syntax

O(n)

Understanding Time Complexity

We want to understand how the time it takes to run a function changes as the input changes.

Specifically, we ask: how does the function's work grow when input size grows?

Scenario Under Consideration

Analyze the time complexity of the following code snippet.

fun printNumbers(n: Int) {
    for (i in 1..n) {
        println(i)
    }
}

This function prints numbers from 1 up to n.

Identify Repeating Operations

Identify the loops, recursion, array traversals that repeat.

• Primary operation: The for-loop that prints each number.
• How many times: It runs exactly n times, once for each number.

How Execution Grows With Input

As n grows, the number of print actions grows the same way.

Input Size (n)	Approx. Operations
10	10 print actions
100	100 print actions
1000	1000 print actions

Pattern observation: The work grows directly with n, so doubling n doubles the work.

Final Time Complexity

Time Complexity: O(n)

This means the time to run the function grows in a straight line with the input size.

Common Mistake

[X] Wrong: "The function runs in constant time because it just prints numbers."

[OK] Correct: Printing happens once for each number, so more numbers mean more work.

Interview Connect

Understanding how loops affect time helps you explain your code clearly and shows you know how programs grow with input.

Self-Check

"What if we changed the function to print only even numbers up to n? How would the time complexity change?"