Josh Wieder

Lets say we have a form. The form is straight-forward: HTML radio buttons that posts to a PHP processing script that saves the results to a database. The radio buttons correspond to bindary responses to questions - Yes/No, True/False. These truth values are mapped to the integers '1' and '0', which are then stored in the database. When such a form is creating new records, this is about as brainless as web-development gets. But things get more complicated when the form is used to update existing records. A useful update form will typically have a few basic features; among them, the option to update all of the data in the form or just some of the data. To do this, we have to check whether a variable is being updated or not. One approach to checking on variable updates is to create an array with all of the variables to be considered, like this:  $stuff = array( 'fee' => $_POST['fee'], 'fi' => $_POST['fi'], ...

What does it mean for an algorithm to be "fast" or "efficient"? When we say an algorithm is fast, we are not referring to an explicitly notation in time, like seconds or minutes. There is a distinction here because of the distinction between hardware and software - performance of a program in real time can be drastically impacted by the hardware it is running on. In order to account for this distinction, while still providing an objective measurement for the efficiency of a program, computer scientists rely on Asymptotic Measurement and a notation format called Big O Notation to describe such measurements. The formal description as a formula is as follows: f(x) ∈ g(x) x o C f(x) ≤ C • g(x) x > x o In less theoretical terms; as the size of your input increases toward infinity, how does the runtime of your program grow? For example, imagine counting the number of characters in a string in the most simple way, by reading each character and summi...