Can you explain the concept of algorithm complexity assessment and why it is important?

Algorithm complexity assessment is a way to understand how the execution time or memory usage of an algorithm changes depending on the size of the input data. The Big O notation is commonly used, which shows the upper bound of growth.

Why is this important:

• It helps choose the most efficient algorithm for a task.
• It allows predicting performance as data volume increases.
• It improves the quality and scalability of the application.

Example: sorting an array of 10 elements and one of 1 million — algorithms with high complexity will take too long on large data.

// Example of complexity assessment
func linearSearch(array: [Int], target: Int) -> Int? {
    for (index, value) in array.enumerated() {
        if value == target {
            return index
        }
    }
    return nil
}
// Complexity O(n), where n is the number of elements in the array