parametric

The approach is similar to parametric builds in jenkins.

Any generics solution has to have fast runtime, because they need to replace the builtin parametric slices and maps.

There was also a parametric CAD application that was used by Lucas(?) for a bit.

June 22 was in fact the day when duckduckgo.com broke 10M daily direct query count, as predicted by non-parametric, fully-automated forecasting.

But that's an utterly terrible analogy to parametric CAD, which is really a touch closer to a kind of end-user programming language.

There's a lot of overlap between a dynamic dispatch mechanism and parametric polymorphism.

Constraint debugging in parametric CAD can occasionally be a frustrating kind of hell.

As Varoufakis explained it, he wants qualitative reforms rather than parametric reforms.

Furthermore, I'm pretty sure that even I would have been faster in a parametric modeler, and I'm a software engineer.

Higher level generator HDLs shine when you want something heavily parametric.

Being a career software developer who has recently learned to use parametric CAD (specifically, Geomagic Design, formerly known as Alibre Design), this is just not true.

In plain English: `search_entry_hashed` is a parametric function.

Look at the "Techniques", the first three are: "Parametric methods, by which the parameters of the distribution are calculated from the data series.[2] The parametric methods are: method of moments method of L-moments[3] Maximum likelihood method[4]" which if you work them out you get exactly what you'd expect.

Parametric polymorphism is something every statically typed programming language should have in 2015.

Parametric CAD is far better about keeping relevant dimension values, formulas, and model constraints right where they're relevant and trivial to visually comprehend in terms of their function in the model.