I understand the code but have a question about how to describe the complexity.
Why is it correct to say it is O(N)? Is that in fact the best way to describe the complexity, or is there an alternate way to do so that captures the subtlety below? I've seen complexities described as O(k + n), for example, where there are 2 inputs. We don't have that in this case, but we do have O(lastvalue - firstval). I understand ultimately it will be linear but not proportional to array size.

In this case where the input is an array, an input of [10,50] is of course smaller than an input of [10,11,15,16,17,19,20].
To my understanding, normally where input is an array, when we say O(N) that would be input length.
Is it not more correct to specify this complexity as O(lastvalue - firstval), however one would say that.
Or am I overthinking.

Hey Jake,
I initially approached this problem a little different than the solution you provided. I knew that since the array was sorted the values within the list would have an interval range from the starting number in the array to the last number in the array. Therefore, I just looped through that range and checked whether or not the current num in the loop is not in the array. If it wasnt, that means its a missing number.

In your opinion does this solution work, or does your solution in looking for the difference between each number in the array to be 1 more efficient?

def missing_numbers(num_arr):
    missing = []
    for num in range(num_arr[0], num_arr[-1]+1):
      if num not in num_arr:
        missing.append(num)
    return missing

In the final solution, since the missing array stores the values which can be at worst n - 2, then the Space Complexity would still be considered O(n)?