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Validation with Java and XML Schema, Part 1

Learn the value of data validation and why pure Java isn't the complete solution for handling it

By Brett Mclaughlin, JavaWorld.com, 09/08/00

As technologies have matured and APIs for Java and other languages have taken more of the burden of low-level coding off your hands (JMS, EJB, and XML are just a few recent examples), business logic has become more important to application coding. With this increase in business logic comes an increase in the specification of data allowed.

Read the whole "Validation with Java and XML Schema" series:



For example, applications no longer just accept orders for shoes; they ensure that the shoe is of a valid size, in stock, and accurately priced. The business rules that must be applied even for a simple shoe store are extremely complex. The user input and the input combination must be validated; those data often result in computed data, which may have to be validated before it is passed on to another application component. With that added complexity, you spend more time writing validation methods. You ensure that a value is a number, a decimal, a dollar amount, that it's not negative, and on, and on, and on.

With servlets and JSP pages sending all submitted parameters as textual values (an array of Java Strings, to be exact), your application must convert to a different data type at every step of user input. That converted data is most likely passed to session beans. The beans can ensure type safety (requiring an int, for example), but not the value range. So validation must occur again. Finally, business logic may need to be applied. (Does Doc Marten make this boot in a size 10?) Only then can computation safely be performed, and results supplied to the user. If you're starting to feel overwhelmed, good! You are starting to see the importance of validation, and why this series might be right for you.

Coarse-grained vs. fine-grained validation

The first step in making your way through the "validation maze" is breaking the validation process into two distinct parts: coarse-grained validation and fine-grained validation. I'll look at both.

Coarse-grained validation is the process of ensuring that data meet the typing criteria for further action. Here, "typing criteria" means basic data constraints such as data type, range, and allowed values. These constraints are independent of other data, and do not require access to business logic. An example of coarse-grained validation is making sure that shoe sizes are positive numbers, smaller than 20, and either whole numbers or half sizes.

Fine-grained validation is the process of applying business logic to values. It typically occurs after coarse-grained validation, and is the final step of preparation, before one either returns results to the user or passes derived values to other application components. An example of fine-grained validation is ensuring that the requested size (already in the correct format because of coarse-grained validation) is valid for the requested brand. V-Form inline skates are only available in whole sizes, so a request for a size 10 1/2 should cause an error. Because that requires interaction with some form of data store and business logic, it is fine-grained validation.

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