The Logic Behind Validating Data

< Day Day Up > The Logic Behind Validating Data We validate things every day—from words in a sentence (to make sure they make sense) to change received from purchases. The concept of validation is a natural and easy one for us to understand. For example, examine the following (U.S.) phone number: 555- 34567. Chances are you quickly recognized the phone number to be invalid. How? Your brain analyzed the phone number and noted that it contained eight digits. After comparing this fact to the rule that defines valid local phone numbers as those that include seven digits, your brain made a determination of true (the number was valid) or false (it was invalid). If you determine that the number is valid, you can place the phone call. If the number is invalid, however, your brain will log an error message—something similar to "That number is wrong. I need to get the correct number and then try to call." If we were to break down the validation process, it would look similar to the following: 1. Define criteria for valid data. 2. Analyze submitted data. 3. Compare this data against defined criteria. 4. Continue if data is valid; determine and note error if data is invalid; resolve and then try again. In ActionScript, this process of analyzing information—comparing it to a set of rules and then determining the data's validity—is known as a validation routine. Just as your brain analyzes data instantaneously, an ActionScript validation routine takes a split second to complete. You usually need to validate data within a Flash application whenever you require the user to enter information into an input text field—for example, on forms (name, address, phone number, and so on) and quizzes (to verify answers) and in e-commerce shopping carts (quantities, sizes, colors, and so on). < Day Day Up >   . < Day Day Up > The Logic Behind Validating Data We validate things every day—from words in a sentence (to make sure they make sense) to change. valid data. 2. Analyze submitted data. 3. Compare this data against defined criteria. 4. Continue if data is valid; determine and note error if data is