Array declaration in Go - Time & Space Complexity

Time Complexity: Array declaration

O(n)

Understanding Time Complexity

When we declare an array in Go, it is important to understand how this affects the program's speed as the array size changes.

We want to know how the time to create an array grows when the array gets bigger.

Scenario Under Consideration

Analyze the time complexity of the following code snippet.

package main

func main() {
    var numbers [100]int
    for i := 0; i < len(numbers); i++ {
        numbers[i] = i * 2
    }
}

This code declares an array of 100 integers and fills it with values by looping through each position.

Identify Repeating Operations

Identify the loops, recursion, array traversals that repeat.

• Primary operation: The for-loop that assigns values to each element in the array.
• How many times: Exactly once for each element, so 100 times in this example.

How Execution Grows With Input

As the array size grows, the number of assignments grows at the same rate.

Input Size (n)	Approx. Operations
10	10 assignments
100	100 assignments
1000	1000 assignments

Pattern observation: The work grows directly with the size of the array; doubling the array doubles the work.

Final Time Complexity

Time Complexity: O(n)

This means the time to fill the array grows in a straight line with the number of elements.

Common Mistake

[X] Wrong: "Declaring an array is instant and does not depend on its size."

[OK] Correct: While declaration reserves space quickly, initializing or filling the array requires time proportional to its size.

Interview Connect

Understanding how array operations scale helps you explain your code choices clearly and shows you know how programs handle data efficiently.

Self-Check

"What if we replaced the array with a slice that grows dynamically? How would the time complexity change?"