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comment How to pick the testing values for parameterized tests for stateless functions?
You're mixing up implementation and specification. I can specify that Clamp() will return value when it is between lowerBound and upperBound, lowerBound when it is less than lowerBound, and upperBound when it is greater than upperBound, an throws an exception when upperBound is less than lowerBound. Without assuming anything about how I'm going to implement this, how can I pick the most convenient values? And I'm looking for a strategy for any stateless function in general that you know the specification but not the implementation of.
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comment How to pick the testing values for parameterized tests for stateless functions?
Almost every paragraph you're making assumptions about the supposed implementation of Clamp(), which you and I don't know (since I haven't implemented it yet). For example, I might make a mistake with signed/unsigned comparisons, or I might distinguish between positive and negative values, and somehow completely forgot about 0. You can't make any assumptions about the implementation. However, I agree that I could specify what Clamp() is supposed to do, but I'm searching for a general way to determine the test values. My mathematical class will contain more functions than just Clamp().
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comment How to pick the testing values for parameterized tests for stateless functions?
While 343 test cases seems like a lot, I'm not saying it is too much or not feasible. Indeed, automation is the way to go here. But the question was more along the lines of: what strategy can I use to pick the best values for my test cases?
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asked How to pick the testing values for parameterized tests for stateless functions?
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answered C# String.format extension method
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comment More efficient way to paginate search results
@AaronKurtzhals Sure, just not my question.
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comment More efficient way to paginate search results
Getting page 16 takes longer than getting page 1, according to this question. It has to count records from the start every time, making it a Schlemiel's algorithm. Maybe its just not that noticeable in small data sets and small offsets.