Throw and rethrow patterns in C Sharp (C#) - Time & Space Complexity

Time Complexity: Throw and rethrow patterns

O(n)

Understanding Time Complexity

When we use throw and rethrow in C#, it affects how many times the program handles errors.

We want to see how the time to handle errors grows as the number of errors or calls increases.

Scenario Under Consideration

Analyze the time complexity of the following code snippet.

void ProcessData(List<int> items)
{
    foreach (var item in items)
    {
        if (item < 0) throw new ArgumentException("Negative value");
    }
}

try
{
    ProcessData(items);
}
catch (Exception ex)
{
    LogError(ex);
    throw; // rethrow preserves stack
}
    

This code processes a list and throws an error if a negative number is found, then rethrows it after logging.

Identify Repeating Operations

Identify the loops, recursion, array traversals that repeat.

• Primary operation: Looping through each item in the list once.
• How many times: Once for each item in the list (n times).

How Execution Grows With Input

As the list gets bigger, the program checks more items one by one.

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

Pattern observation: The number of checks grows directly with the number of items.

Final Time Complexity

Time Complexity: O(n)

This means the time to process grows in a straight line with the number of items.

Common Mistake

[X] Wrong: "Rethrowing an exception repeats the whole loop again."

[OK] Correct: Rethrow only passes the error up; it does not restart the loop or repeat processing.

Interview Connect

Understanding how throw and rethrow affect program flow helps you explain error handling clearly and confidently.

Self-Check

"What if we replaced 'throw;' with 'throw ex;' inside the catch? How would the time complexity change?"