--- Phil Steitz <[EMAIL PROTECTED]> wrote:
> To close out BZ #28829, I need to add some degenerate test cases to
> BinomialDistributionTest. As I started to do this, I realized that adding
> more test points would be easier and we could eliminate duplication of
> code across test classes in the distributions package if we defined
> abstract test classes for discrete and continuous distributions that
> provided generic verification methods. The setup for the discrete case
> looks like this:
>
> Abstract base class for [EMAIL PROTECTED] DiscreteDistribution} tests.
> <p>
> To create a concrete test class for a discrete distribution implementation,
> implement makeDistribution() to return a distribution instance to use in
> tests and each of the test data generation methods below. In each case,
> the test points and test values arrays returned represent parallel arrays
> of inputs and expected values for the distribution returned by
> makeDistribution().
> <p>
> makeDensityTestPoints() -- arguments used to test probability density
> calculation
> makeDensityTestValues() -- expected probability densities
> makeCumulativeTestPoints() -- arguments used to test cumulative probabilities
> makeCumulativeTestValues() -- expected cumulative probabilites
> makeInverseCumulativeTestPoints() -- arguments used to test inverse cdf
> evaluation
> makeInverseCumulativeTestValues() -- expected inverse cdf values
>
> Then one default method for each type of test runs through the test points
> / expected values and checks the test instance. To support tests using
> multiple instances, setXxx methods would also be provided for the instance
> and test data arrays. Similar setup for continuous. This will make it
> easier to add more test cases (including adding missing tests for discrete
> pdf calculations) and simplify development of new distribution test
> classes. Any objections?
>
> Phil
Sounds very reasonable to me.
Al
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