JuliaGaussianProcesses / JuliaGaussianProcesses/KernelFunctions.jl

Tests checking the metric are unhelpful

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Dominant language
Julia
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275
Forks
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No merged PRs in 30d

Description

There are quite a lot of tests that check that metric(kernel) returns a particular metric. It's not clear to me how much value these tests have.

It probably makes sense to ensure that SimpleKernels do implement metric, and return a valid type of metric, but I don't think that we should be testing that they return a specific metric, as this feels like writing a test is basically the same code as the code it's testing, which I believe generally gives a false sense of security.

I'm pro- testing that kernels yield the correct numerical values for certain specific inputs / parameters, or that they are the same as other kernels for particular settings (e.g. gamma-exponential and EQ / exponential) as with this this type of test you're typically not just writing out your source code in your tests.

What are people's thoughts?

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Research direction

Search the test suite for checks that metric(kernel) returns a particular metric, then review the SimpleKernel and metric discussion in this issue. The work is done when the project has a decided, consistent testing approach that preserves numerical and equivalence checks while resolving the disputed specific-metric tests.

Written by the indexing model from the issue text.

Assessment

Tech stack
julia
Domain
machine-learning
Issue type
Refactor
Difficulty
5/5
Estimated time
Over a week
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
25/100

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