For today’s post we’re going to delve into one of the least talked about but extremely common tasks a software developer works with, input validation, or error checking as its more commonly referred to as. Input validation is defined as taking what a user enters on screen, verifying it meets certain requirements, and returning a message to the user if it fails validation.
Let’s say you have a web page that requires a user to enter their zip code as part of account creation. What are the possible paths the user might take? Let’s list them:
- Success: The user enters a 5-digit zip code
- Error #1: The user leaves the zip code blank
- Error #2: The user enters a non-number, such as “Hello”
- Error #3: The user enters a zip code that has less than 5 digits such as “93”
- Error #4: The user enters a zip code that has greater than 5 digits such as “9319299”
- Error #5: The user enters a non-existent zip code such as “00000”
Let’s further add the conditions that the application has been developed using the common three tiered architecture pattern with a web-based HTML UI, a java-based application server, and a SQL-based database server.
The first question to ask is, what needs to be validated on which levels?
- Top Tier: User Interface Validation
Stepping away from zip code for a second, let’s say you want to know the user’s birthday. You could ask them to enter it as a text field such as “10/11/1970” or, more commonly, ask them to use drop down menus to select the month, the day, and the year. The first type of input, where you give the user a lot of control such as a text field is referred to as unstructured input. The second type of input, where you bound the user’s choices to a fixed number of inputs is referred to as structured input. It should go without saying that structured input is far easier for a developer to work with than unstructured since the ‘number of places things can go wrong’ is significantly reduced.
Turning back to the zip code example, a structured input version might have a drop-down of every zip code in the country. That would certainly limit users from entering bad data and reduce most the errors above, but there are nearly 43,000 zip code in the US! The drop-down box would be hard to navigate, not to mention the bandwidth costs of sending every user the list.
For zip code input, we are stuck with unstructured input, but there are ways to reduce the chaotic nature of the input. For example, we could set an HTML width of 5 characters preventing the user from entering more than 5 digits, thereby preventing Error #4 all together.
- Middle Tier: Server side validation
As discussed, unless you have 100% control of a front-end application, which I can argue you never have, things can always reach the middle tier application server that are invalid. For example, a user could be connecting via a web service or by typing in URLs in a browser window. In both of these cases there is no front end to validate the user’s input. Therefore, the primary job of the application server is to provide services that handle all data input from clients and properly store this information in the database.
It is inferred by this logic, then, that the applications server needs someway of reporting errors to the its user. For example, if the zip code is entered incorrectly and discovered on the middle tier, the application server should send a nice, clean message to the user reporting the problem. When a developer forgets to handle this properly, you end up with web pages with ugly stack traces that I’m sure most of you have seen from time to time. In those instances, the developer forgot to properly encapsulate an error message with a user friendly one. It’s a good practice to put a large ‘catch-all’ around each application server entry point, so that in the event the developer missed taking care of an error, the user sees a generic ‘General System Error’ message. While generic messages such as this may not help the user out, it is far better than having them see a huge stack trace on the screen, which may give them private knowledge of the system such as source code paths and method names.
You may have noticed I skipped validating Error #5 on the UI tier, and with good reason. Although zip codes in the US may be 5 digits long, not all 5 digit long numbers are zip codes (logic 101)! For example, ‘00000’ is not a zip code in any state. In order to validate Error #5, you need a database table listing all possible zip codes to check again. Clearly, this is something that should not be done on the UI side since it would require the download of a long list of zip codes. A further validation might be to take the city and state a user enters and verify they belong to a particular zip code. The problem with such excessive validation is that if you’re database less than 100% accurate, the users may have issues in which a valid zip code is declared invalid, or a false positive to use testing terminology.
- Bottom Tier: Database validation
The final validation is the place where the data ultimately ends up: the database. It is most often accomplish in the form of structured fields or uniqueness constraints. Regardless of whether the input is validated on the front or middle tier, the database ultimately owns the data and its rules cannot be violated.
If the database is so powerful, why not just do all input validation within the database? In the past, people have tried and the short answer is, performance suffers and it is difficult to maintain. For example, you shouldn’t need to go down all 3 tiers to check that zip code is a number; that sort of thing can be easily validated on the first two tiers. You do, on the other hand, need to go down all three tiers to check if a username is unique since it requires the knowledge from the databases to validate. That doesn’t mean you should just insert a user and wait for the database to fail, you should always check for possible errors ahead of time and catch them gracefully before moving on to the next level.
There are times, though, where the database validation is going to throw errors the other two layers cannot possibly check. For example, let’s say two users try to insert a a record at the same time with the same username ‘MrWidget’ and this field is declared UNIQUE in the database. Both users checked ahead of time to see if ‘MrWidget’ was available, found that the username was free, and committed to creating accounts with username ‘MrWidget’. Unfortunately, only one of these users will get name ‘MrWidget’, the other will get an error message. These race conditions are not very common in most systems, but are something your system should be designed to detect and handle when they do happen. A correct solution here would be to allow the user that submitted first to proceed and display a friendly error message to the second user alerting them the name is no longer available. This is also a good example of where a generic system exception is not going to help the user correct their situation since the username.