The point is that an interface should help you to both ignore and understand the underlying implementation. I'm not sure I understand your point about data and transport, since most interfaces (e.g. names) don't touch the network. Are these just synonyms for interface and implementation?
It's very plausible that these techniques could be used to fix the output of a CSG library that uses floating point math, but I'm not sure what the specifics would look like. If anyone has ideas in that vein, I'd be very interested to hear them.
Hi, author here. I looked into that side of things, but CGAL only offers exact precision implementations for lines and circular arcs. The fact that Bézier curves are left as an exercise for the reader is further proof of the disconnect between computational geometry and modern computer graphics.
By forcing the GC to run in between tests, basically. The README for the benchmarking tool describes it in more detail: https://github.com/hugoduncan/criterium.
I tried to include these, but it wasn’t immediately obvious how to construct them from outside Scala without CanBuildFrom. If anyone wants to open a PR or even provide a few hints, I’d be happy to update the benchmarks.
You probably saw my response in that thread, where I said that the dramatic performance improvements in lookup speed reported by the CHAMP paper were mostly because they were comparing apples to oranges.
However, Clojure's equality semantics only really help in some niche situations (where you want to be able to use ints, floats, and bignums interchangeably, mostly), so making the equality semantics configurable would be a huge win for all sorts of applications.
Also, lookup is not the only performance win that CHAMP offers: https://github.com/lacuna/bifurcan/blob/master/doc/benchmark.... One thing the approach makes possible, which wasn't explored in the paper, is the ability to do union/difference/intersection operations structurally, rather than just iterating over each element in the set.
None of these improvements are so overwhelming that they take priority over everything else. Clojure's data structures are still really well made. Given how data-focused the language is, however, I think these improvements are more compelling than everything that's been added to the language in the last five years other than `clojure.spec`.
The chance of my implementation being folded into Clojure, as opposed to whatever Rich writes himself, is definitely tiny. But there's no telling when he might get around to it, so the best way to stay sane is to assume it will never happen.
Clojure occupies a really nice local maximum, and I don't think any other language is trying to compete for that niche. Since Clojure is just a Java library, it's relatively easy for you to extend or replace any part of it, so I don't think the future is a concern for anyone who enjoys the language and is motivated to use it.
Rather, I worry about the growth of the community, since that's largely predicated on the out-of-the-box experience. As an author and consultant who is focused on Clojure, that affects me far more than a company which builds its product using Clojure (assuming you're willing to hire people with an interest in FP and teach them the rest in their first month). I don't claim expertise in how to grow a community around a language, but it seems to be at best a part-time job for the people at Cognitect, which is not ideal.
Clojure is the language I'm most productive in. At the beginning of the year I quit my job to write a book about Clojure [1], do some consulting, and build a developer tool I've been talking about for a few years.
For the tool, I'm using a client/server model, and on the client side latency is a huge concern, so I'm using Java. Java is basically assembler for the JVM, and has extremely predictable performance characteristics. Where performance is a non-issue, or I only care about throughput, I'm using Clojure, because it's much more expressive. I think the tradeoffs of the two languages are very complementary, but also much less extreme than, say, Ruby and C.
I find the inertia of the core implementation of the language annoying, even if it's not a huge problem for most applications. Clojure's immutable data structures were world-class when the language was first released ten years ago, but there have been a number of papers which detail improved approaches since then. I've implemented most or all of them [2], but the chance of getting these back into Clojure is effectively nil. That doesn't affect me (I can just use my own data structures), but it does give me some concern as to where the language will be after another ten years.
The lookup performance gain is largely due to the CHAMP implementation using the default Java equality semantics, while Clojure's maps use Clojure's more expensive equality semantics. See https://github.com/lacuna/bifurcan/blob/master/doc/benchmark... for a more in depth illustration of this.
However, it is still a meaningful incremental improvement over Clojure's implementation for iteration and equality checks, among others.