Rethrowing functions in Swift - Time & Space Complexity

Time Complexity: Rethrowing functions

O(n)

Understanding Time Complexity

When using rethrowing functions in Swift, it's important to see how the time cost changes as input grows.

We want to know how the number of steps grows when the function calls other functions that might throw errors.

Scenario Under Consideration

Analyze the time complexity of the following code snippet.

func performOperations(_ operations: [() throws -> Void]) rethrows {
    for operation in operations {
        try operation()
    }
}

// Example usage:
// performOperations([op1, op2, op3])

This code runs a list of operations that might throw errors, passing the error up if any occur.

Identify Repeating Operations

• Primary operation: Looping through each operation in the array and calling it.
• How many times: Once for each operation in the input list.

How Execution Grows With Input

Each operation is called once, so the total steps grow as the number of operations grows.

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

Pattern observation: The work grows directly with the number of operations.

Final Time Complexity

Time Complexity: O(n)

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

Common Mistake

[X] Wrong: "Rethrowing functions add extra hidden loops or slow down the code significantly."

[OK] Correct: Rethrowing just passes errors up; it does not add extra loops or repeat work beyond the original calls.

Interview Connect

Understanding how rethrowing affects time helps you explain error handling clearly and confidently in real coding situations.

Self-Check

"What if the operations array contained nested calls that also rethrow? How would that affect the overall time complexity?"