Validate all Inbound Data
Odd errors can occur when you get data that doesn’t fit the format, but matches close enough not to fail outright. This type of error can be really hard to unravel. Preventing these messy errors, it is a good practice to implement a validation process before processing the data. Some integration technologies come with validation, if yours doesn’t you should pre-process inbound data for validation.
In addition to this, pre validation can be used as a way to catch and handle other errors early. Leveraging pre-processing with validation and error handling can give you a one stop place to catch, and report or correct systemic problems.
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February 15th, 2010 at 12:47 pm
When I think of ‘input validation’, “Postel’s Prescription…” comes to mind:
http://www.faqs.org/docs/artu/ch01s06.html#id2878578
http://catb.org/jargon/html/P/Postels-Prescription.html
“Be liberal in what you accept, and conservative in what you send”. Postel was speaking of network service programs, but the underlying idea is more general. Well-designed programs cooperate with other programs by making as much sense as they can from ill-formed inputs; they either fail noisily or pass strictly clean and correct data to the next program in the chain.