Continue statement in Go - Time & Space Complexity

Time Complexity: Continue statement

O(n)

Understanding Time Complexity

Let's see how the continue statement affects the time a program takes to run.

We want to know if skipping some steps changes how long the code runs as input grows.

Scenario Under Consideration

Analyze the time complexity of the following code snippet.

for i := 0; i < n; i++ {
    if i%2 == 0 {
        continue
    }
    // some constant time work here
}
    

This code loops from 0 to n-1, but skips the work when i is even using continue.

Identify Repeating Operations

Identify the loops, recursion, array traversals that repeat.

• Primary operation: A single loop running n times.
• How many times: The loop runs n times, but work inside runs about half the times.

How Execution Grows With Input

Even though some steps are skipped, the loop still checks all n items.

Input Size (n)	Approx. Operations
10	10 loop checks, 5 work executions
100	100 loop checks, 50 work executions
1000	1000 loop checks, 500 work executions

Pattern observation: The total steps grow linearly with n, skipping work only halves some operations.

Final Time Complexity

Time Complexity: O(n)

This means the time grows directly with the input size, even if some steps are skipped.

Common Mistake

[X] Wrong: "Using continue makes the loop run faster and changes time complexity to O(n/2)."

[OK] Correct: Even if some work is skipped, the loop still runs n times, so time still grows linearly with n.

Interview Connect

Understanding how continue affects loops helps you explain code efficiency clearly and shows you know how skipping steps impacts performance.

Self-Check

What if we replaced continue with break? How would the time complexity change?