CowboyRobot writes: Andrew Koenig at Dr. Dobb's argues that by looking at a program's structure — as opposed to only looking at output — we can sometimes predict circumstances in which it is particularly likely to fail. "For example, any time a program decides to use one or two (or more) algorithms depending on an aspect of its input such as size, we should verify that it works properly as close as possible to the decision boundary on both sides. I've seen quite a few programs that impose arbitrary length limits on, say, the size of an input line or the length of a name. I've also seen far too many such programs that fail when they are presented with input that fits the limit exactly, or is one greater (or less) than the limit. If you know by inspecting the code what those limits are, it is much easier to test for cases near the limits."
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