Enum entries iteration in Kotlin - Time & Space Complexity

Time Complexity: Enum entries iteration

O(n)

Understanding Time Complexity

When we loop through all entries of an enum, we want to know how the time needed changes as the number of entries grows.

We ask: How does the work grow when the enum has more items?

Scenario Under Consideration

Analyze the time complexity of the following code snippet.

enum class Color {
    RED, GREEN, BLUE, YELLOW
}

fun printColors() {
    for (color in Color.values()) {
        println(color)
    }
}

This code loops through all enum entries and prints each one.

Identify Repeating Operations

Identify the loops, recursion, array traversals that repeat.

• Primary operation: Looping through all enum entries using Color.values().
• How many times: Once for each enum entry, so as many times as there are entries.

How Execution Grows With Input

As the number of enum entries grows, the loop runs once per entry, so the work grows directly with the number of entries.

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

Pattern observation: The work increases evenly as the number of enum entries increases.

Final Time Complexity

Time Complexity: O(n)

This means the time grows in a straight line with the number of enum entries.

Common Mistake

[X] Wrong: "Looping over enum entries is constant time because enums are fixed."

[OK] Correct: Even though enums have fixed entries, the loop still runs once per entry, so time grows with the number of entries.

Interview Connect

Understanding how looping over enum entries scales helps you explain performance clearly and shows you know how to analyze simple loops well.

Self-Check

"What if we nested another loop inside to compare each enum entry with every other? How would the time complexity change?"